taoxiangdong
4 years ago
parent
53f881572e
commit
1c6ba29523
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../../proto/ge_api.proto
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/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved.
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*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* Apache License for more details at
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* http://www.apache.org/licenses/LICENSE-2.0
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*/
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syntax = "proto3";
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package domi;
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message ModelTaskDef {
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string version = 1;
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map<string, string> attr = 9; // Extended field
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repeated TaskDef task = 10;
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uint64 memory_size = 11;
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uint32 stream_num = 12;
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uint32 event_num = 13;
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uint64 weight_size = 14;
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repeated bytes op = 15; // input/output opdef in bytes
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uint64 base_addr = 16; // base addr
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uint64 weight_addr = 17; // weight addr
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uint32 batch_num = 18;
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}
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message TaskDef {
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uint32 id = 1;
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uint32 type = 2;
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uint32 stream_id = 10;
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uint32 event_id = 11;
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KernelDef kernel = 20;
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KernelExDef kernel_ex = 21;
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KernelHcclDef kernel_hccl = 25;
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EventExDef event_ex = 26;
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LogTimeStampDef log_timestamp = 28;
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uint32 label_id = 30;
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MemcpyAsyncDef memcpy_async = 31;
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StreamSwitchDef stream_switch = 32;
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StreamActiveDef stream_active = 33;
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bytes private_def = 34;
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uint64 ops_kernel_store_ptr = 35; // adjustments to other fields in the future
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StreamSwitchNDef stream_switch_n = 36;
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LabelSetDef label_set = 37;
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LabelGotoExDef label_goto_ex = 38;
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LabelSwitchByIndexDef label_switch_by_index = 39;
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}
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message KernelDef {
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KernelContext context = 1;
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string stub_func = 10;
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uint32 block_dim = 11;
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uint32 args_size = 12;
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bytes args = 13;
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bytes sm_desc = 14;
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bytes flowtable = 15;
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string so_name = 16;
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string kernel_name = 17;
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bytes kernel_ext_info = 18;
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uint32 kernel_ext_info_size = 19;
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}
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message KernelContext {
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uint32 kernel_type = 1;
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uint32 op_id = 2; // OP type in CCE
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uint32 kernel_func_id = 3;
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uint32 op_index = 4; // TE/Custom operator
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bool is_flowtable = 5; // Identify whether args is a flowtable structure
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bytes args_offset = 6; // args offset information
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uint32 args_count = 7; // args count
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repeated uint32 origin_op_index = 8;
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}
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message KernelExDef {
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uint32 flags = 1;
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uint32 op_index = 4;
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uint32 args_size = 12;
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bytes args = 13;
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bytes task_info = 14; // serialized nodeDef, funcDef, inputoutput
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uint32 task_info_size = 15;
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bytes kernel_ext_info = 16;
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uint32 kernel_ext_info_size = 17;
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}
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message KernelHcclDef {
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uint32 op_index = 8;
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string hccl_type = 9;
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}
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message EventExDef {
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uint32 op_index = 1;
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uint32 event_type = 2;
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}
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message LogTimeStampDef {
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uint64 logid = 1;
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bool notify = 2;
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uint32 flat = 3;
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}
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message MemcpyAsyncDef {
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uint64 dst = 1;
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uint64 dst_max = 2;
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uint64 src = 3;
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uint64 count = 4;
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uint32 kind = 5;
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uint32 op_index = 6;
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}
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message StreamSwitchDef {
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uint32 op_index = 1;
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uint32 true_stream_id = 2;
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int64 value = 3;
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uint64 value_ptr = 4;
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uint32 data_type = 5;
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}
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message StreamActiveDef {
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uint32 op_index = 1;
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uint32 active_stream_id = 2;
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}
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message StreamSwitchNDef {
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uint32 op_index = 1;
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uint32 size = 2;
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repeated int64 target_value = 3;
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repeated uint32 true_stream_id = 4;
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uint32 element_size = 5;
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uint32 data_type = 6;
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}
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message LabelSetDef {
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uint32 op_index = 1;
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uint32 label_id = 2;
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uint32 model_id = 3;
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}
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message LabelGotoExDef {
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uint32 op_index = 1;
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uint32 label_id = 2;
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uint32 model_id = 3;
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}
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message LabelSwitchByIndexDef {
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uint32 op_index = 1;
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uint32 label_max = 2;
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}
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File diff suppressed because it is too large
Load Diff
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syntax = "proto3";
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package aicpu.dump;
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message Shape {
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repeated uint64 dim = 1;
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}
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message Output {
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int32 data_type = 1;
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int32 format = 2;
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Shape shape = 3;
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uint64 address = 4;
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string original_name = 5;
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int32 original_output_index = 6;
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int32 original_output_data_type = 7;
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int32 original_output_format = 8;
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uint64 size = 9;
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}
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message Input {
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int32 data_type =1;
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int32 format = 2;
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Shape shape = 3;
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uint64 address = 4;
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uint64 size = 5;
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}
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enum BufferType {
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L1 = 0;
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}
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message OpBuffer {
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BufferType buffer_type = 1;
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uint64 address = 2;
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uint64 size = 3;
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}
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message Op {
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string op_name = 1;
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string op_type = 2;
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}
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message Task {
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uint32 task_id = 1;
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uint32 stream_id = 2;
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Op op = 3;
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repeated Output output = 4;
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bool end_graph = 5;
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repeated Input input = 6;
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repeated OpBuffer buffer = 7;
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}
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message OpMappingInfo {
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string dump_path = 1;
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oneof model_name_param {
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string model_name = 2;
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}
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oneof model_id_param {
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uint32 model_id = 3;
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}
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oneof step_id {
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uint64 step_id_addr = 4;
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}
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oneof iterations_per_loop {
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uint64 iterations_per_loop_addr = 5;
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}
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oneof loop_cond {
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uint64 loop_cond_addr = 6;
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}
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uint32 flag = 7; // 0x01 load, 0x00 unload
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repeated Task task = 8;
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string dump_step = 9;
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}
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@ -0,0 +1,165 @@
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/* Copyright (C) 2018. Huawei Technologies Co., Ltd. All rights reserved.
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*
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* This program is free software; you can redistribute it and/or modify
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* it under the terms of the Apache License Version 2.0.You may not use this file except in compliance with the License.
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*
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* This program is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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* Apache License for more details at
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* http://www.apache.org/licenses/LICENSE-2.0
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*/
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syntax = "proto3";
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package domi;
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message ModelTaskDef {
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string version = 1;
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map<string, string> attr = 9; // Extended field
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repeated TaskDef task = 10;
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uint64 memory_size = 11;
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uint32 stream_num = 12;
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uint32 event_num = 13;
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uint64 weight_size = 14;
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repeated bytes op = 15; // input/output opdef in bytes
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uint64 base_addr = 16; // base addr
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uint64 weight_addr = 17; // weight addr
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uint32 batch_num = 18;
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}
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message TaskDef {
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uint32 id = 1;
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uint32 type = 2;
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uint32 stream_id = 10;
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uint32 event_id = 11;
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KernelDef kernel = 20;
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KernelExDef kernel_ex = 21;
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KernelHcclDef kernel_hccl = 25;
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EventExDef event_ex = 26;
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LogTimeStampDef log_timestamp = 28;
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uint32 label_id = 30;
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MemcpyAsyncDef memcpy_async = 31;
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StreamSwitchDef stream_switch = 32;
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StreamActiveDef stream_active = 33;
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bytes private_def = 34;
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uint64 ops_kernel_store_ptr = 35; // adjustments to other fields in the future
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StreamSwitchNDef stream_switch_n = 36;
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LabelSetDef label_set = 37;
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LabelGotoExDef label_goto_ex = 38;
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LabelSwitchByIndexDef label_switch_by_index = 39;
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}
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message KernelDef {
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KernelContext context = 1;
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string stub_func = 10;
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uint32 block_dim = 11;
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uint32 args_size = 12;
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bytes args = 13;
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bytes sm_desc = 14;
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bytes flowtable = 15;
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string so_name = 16;
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string kernel_name = 17;
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bytes kernel_ext_info = 18;
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uint32 kernel_ext_info_size = 19;
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}
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message KernelContext {
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uint32 kernel_type = 1;
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uint32 op_id = 2; // OP type in CCE
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uint32 kernel_func_id = 3;
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uint32 op_index = 4; // TE/Custom operator
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bool is_flowtable = 5; // Identify whether args is a flowtable structure
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bytes args_offset = 6; // args offset information
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uint32 args_count = 7; // args count
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repeated uint32 origin_op_index = 8;
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}
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message KernelExDef {
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uint32 flags = 1;
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uint32 op_index = 4;
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uint32 args_size = 12;
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bytes args = 13;
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bytes task_info = 14; // serialized nodeDef, funcDef, inputoutput
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uint32 task_info_size = 15;
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bytes kernel_ext_info = 16;
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uint32 kernel_ext_info_size = 17;
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}
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message KernelHcclDef {
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uint32 op_index = 8;
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string hccl_type = 9;
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}
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message EventExDef {
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uint32 op_index = 1;
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uint32 event_type = 2;
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}
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message LogTimeStampDef {
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uint64 logid = 1;
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bool notify = 2;
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uint32 flat = 3;
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}
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message MemcpyAsyncDef {
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uint64 dst = 1;
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uint64 dst_max = 2;
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uint64 src = 3;
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uint64 count = 4;
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uint32 kind = 5;
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uint32 op_index = 6;
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}
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message StreamSwitchDef {
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uint32 op_index = 1;
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uint32 true_stream_id = 2;
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int64 value = 3;
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uint64 value_ptr = 4;
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uint32 data_type = 5;
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}
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message StreamActiveDef {
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uint32 op_index = 1;
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uint32 active_stream_id = 2;
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}
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message StreamSwitchNDef {
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uint32 op_index = 1;
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uint32 size = 2;
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repeated int64 target_value = 3;
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repeated uint32 true_stream_id = 4;
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uint32 element_size = 5;
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uint32 data_type = 6;
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}
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message LabelSetDef {
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uint32 op_index = 1;
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uint32 label_id = 2;
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uint32 model_id = 3;
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}
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message LabelGotoExDef {
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uint32 op_index = 1;
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uint32 label_id = 2;
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uint32 model_id = 3;
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}
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message LabelSwitchByIndexDef {
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uint32 op_index = 1;
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uint32 label_max = 2;
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}
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syntax = "proto3";
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package domi.tensorflow;
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option cc_enable_arenas = true;
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option java_outer_classname = "AttrValueProtos";
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option java_multiple_files = true;
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option java_package = "org.tensorflow.framework";
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import "tensor.proto";
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import "tensor_shape.proto";
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import "types.proto";
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// Protocol buffer representing the value for an attr used to configure an Op.
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// Comment indicates the corresponding attr type. Only the field matching the
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// attr type may be filled.
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message AttrValue {
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// LINT.IfChange
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message ListValue {
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repeated bytes s = 2; // "list(string)"
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repeated int64 i = 3 [packed = true]; // "list(int)"
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repeated float f = 4 [packed = true]; // "list(float)"
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repeated bool b = 5 [packed = true]; // "list(bool)"
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repeated DataType type = 6 [packed = true]; // "list(type)"
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repeated TensorShapeProto shape = 7; // "list(shape)"
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repeated TensorProto tensor = 8; // "list(tensor)"
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repeated NameAttrList func = 9; // "list(attr)"
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}
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// LINT.ThenChange(https://www.tensorflow.org/code/tensorflow/c/c_api.cc)
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oneof value {
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bytes s = 2; // "string"
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int64 i = 3; // "int"
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float f = 4; // "float"
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bool b = 5; // "bool"
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DataType type = 6; // "type"
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TensorShapeProto shape = 7; // "shape"
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TensorProto tensor = 8; // "tensor"
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ListValue list = 1; // any "list(...)"
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// "func" represents a function. func.name is a function's name or
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// a primitive op's name. func.attr.first is the name of an attr
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// defined for that function. func.attr.second is the value for
|
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// that attr in the instantiation.
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NameAttrList func = 10;
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// This is a placeholder only used in nodes defined inside a
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// function. It indicates the attr value will be supplied when
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// the function is instantiated. For example, let us suppose a
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// node "N" in function "FN". "N" has an attr "A" with value
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// placeholder = "foo". When FN is instantiated with attr "foo"
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// set to "bar", the instantiated node N's attr A will have been
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// given the value "bar".
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||||
string placeholder = 9;
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||||
}
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||||
}
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||||
|
||||
// A list of attr names and their values. The whole list is attached
|
||||
// with a string name. E.g., MatMul[T=float].
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||||
message NameAttrList {
|
||||
string name = 1;
|
||||
map<string, AttrValue> attr = 2;
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||||
}
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@ -0,0 +1,100 @@
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syntax = "proto3";
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package domi.tensorflow;
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option cc_enable_arenas = true;
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option java_outer_classname = "FunctionProtos";
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option java_multiple_files = true;
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option java_package = "org.tensorflow.framework";
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|
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import "attr_value.proto";
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import "node_def.proto";
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import "op_def.proto";
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// A library is a set of named functions.
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message FunctionDefLibrary {
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repeated FunctionDef function = 1;
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repeated GradientDef gradient = 2;
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}
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// A function can be instantiated when the runtime can bind every attr
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// with a value. When a GraphDef has a call to a function, it must
|
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// have binding for every attr defined in the signature.
|
||||
// * device spec, etc.
|
||||
message FunctionDef {
|
||||
// The definition of the function's name, arguments, return values,
|
||||
// attrs etc.
|
||||
OpDef signature = 1;
|
||||
|
||||
// Attributes specific to this function definition.
|
||||
map<string, AttrValue> attr = 5;
|
||||
|
||||
// NOTE: field id 2 deleted on Jan 11, 2017, GraphDef version 21.
|
||||
reserved 2;
|
||||
|
||||
// In both of the following fields, there is the need to specify an
|
||||
// output that is used as either the input to another node (in
|
||||
// `node_def`) or as a return value of the function (in `ret`).
|
||||
// Unlike the NodeDefs in GraphDef, we need to be able to specify a
|
||||
// list in some cases (instead of just single outputs). Also, we
|
||||
// need to be able to deal with lists of unknown length (so the
|
||||
// output index may not be known at function definition time). So
|
||||
// we use the following format instead:
|
||||
// * "fun_in" where "fun_in" is the name of a function input arg in
|
||||
// the `signature` field above. This represents that input, whether
|
||||
// it is a single tensor or a list.
|
||||
// * "fun_in:0" gives the first element of a function input arg (a
|
||||
// non-list input is considered a list of length 1 for these
|
||||
// purposes).
|
||||
// * "node:out" where "node" is the name of a node in `node_def` and
|
||||
// "out" is the name one of its op's output arguments (the name
|
||||
// comes from the OpDef of the node's op). This represents that
|
||||
// node's output, whether it is a single tensor or a list.
|
||||
// Note: We enforce that an op's output arguments are never
|
||||
// renamed in the backwards-compatibility test.
|
||||
// * "node:out:0" gives the first element of a node output arg (a
|
||||
// non-list output is considered a list of length 1 for these
|
||||
// purposes).
|
||||
//
|
||||
// NOT CURRENTLY SUPPORTED (but may be in the future):
|
||||
// * "node:out:-1" gives last element in a node output list
|
||||
// * "node:out:1:" gives a list with all but the first element in a
|
||||
// node output list
|
||||
// * "node:out::-1" gives a list with all but the last element in a
|
||||
// node output list
|
||||
|
||||
// The body of the function. Unlike the NodeDefs in a GraphDef, attrs
|
||||
// may have values of type `placeholder` and the `input` field uses
|
||||
// the "output" format above.
|
||||
|
||||
// By convention, "op" in node_def is resolved by consulting with a
|
||||
// user-defined library first. If not resolved, "func" is assumed to
|
||||
// be a builtin op.
|
||||
repeated NodeDef node_def = 3;
|
||||
|
||||
// A mapping from the output arg names from `signature` to the
|
||||
// outputs from `node_def` that should be returned by the function.
|
||||
map<string, string> ret = 4;
|
||||
}
|
||||
|
||||
// GradientDef defines the gradient function of a function defined in
|
||||
// a function library.
|
||||
//
|
||||
// A gradient function g (specified by gradient_func) for a function f
|
||||
// (specified by function_name) must follow the following:
|
||||
//
|
||||
// The function 'f' must be a numerical function which takes N inputs
|
||||
// and produces M outputs. Its gradient function 'g', which is a
|
||||
// function taking N + M inputs and produces N outputs.
|
||||
//
|
||||
// I.e. if we have
|
||||
// (y1, y2, ..., y_M) = f(x1, x2, ..., x_N),
|
||||
// then, g is
|
||||
// (dL/dx1, dL/dx2, ..., dL/dx_N) = g(x1, x2, ..., x_N,
|
||||
// dL/dy1, dL/dy2, ..., dL/dy_M),
|
||||
// where L is a scalar-value function of (x1, x2, ..., xN) (e.g., the
|
||||
// loss function). dL/dx_i is the partial derivative of L with respect
|
||||
// to x_i.
|
||||
message GradientDef {
|
||||
string function_name = 1; // The function name.
|
||||
string gradient_func = 2; // The gradient function's name.
|
||||
}
|
||||
@ -0,0 +1,56 @@
|
||||
syntax = "proto3";
|
||||
|
||||
package domi.tensorflow;
|
||||
option cc_enable_arenas = true;
|
||||
option java_outer_classname = "GraphProtos";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "org.tensorflow.framework";
|
||||
|
||||
import "node_def.proto";
|
||||
import "function.proto";
|
||||
import "versions.proto";
|
||||
|
||||
// Represents the graph of operations
|
||||
message GraphDef {
|
||||
repeated NodeDef node = 1;
|
||||
|
||||
// Compatibility versions of the graph. See core/public/version.h for version
|
||||
// history. The GraphDef version is distinct from the TensorFlow version, and
|
||||
// each release of TensorFlow will support a range of GraphDef versions.
|
||||
VersionDef versions = 4;
|
||||
|
||||
// Deprecated single version field; use versions above instead. Since all
|
||||
// GraphDef changes before "versions" was introduced were forward
|
||||
// compatible, this field is entirely ignored.
|
||||
int32 version = 3 [deprecated = true];
|
||||
|
||||
// EXPERIMENTAL. DO NOT USE OR DEPEND ON THIS YET.
|
||||
//
|
||||
// "library" provides user-defined functions.
|
||||
//
|
||||
// Naming:
|
||||
// * library.function.name are in a flat namespace.
|
||||
// NOTE: We may need to change it to be hierarchical to support
|
||||
// different orgs. E.g.,
|
||||
// { "/google/nn", { ... }},
|
||||
// { "/google/vision", { ... }}
|
||||
// { "/org_foo/module_bar", { ... }}
|
||||
// map<string, FunctionDefLib> named_lib;
|
||||
// * If node[i].op is the name of one function in "library",
|
||||
// node[i] is deemed as a function call. Otherwise, node[i].op
|
||||
// must be a primitive operation supported by the runtime.
|
||||
//
|
||||
//
|
||||
// Function call semantics:
|
||||
//
|
||||
// * The callee may start execution as soon as some of its inputs
|
||||
// are ready. The caller may want to use Tuple() mechanism to
|
||||
// ensure all inputs are ready in the same time.
|
||||
//
|
||||
// * The consumer of return values may start executing as soon as
|
||||
// the return values the consumer depends on are ready. The
|
||||
// consumer may want to use Tuple() mechanism to ensure the
|
||||
// consumer does not start until all return values of the callee
|
||||
// function are ready.
|
||||
FunctionDefLibrary library = 2;
|
||||
};
|
||||
@ -0,0 +1,14 @@
|
||||
syntax = "proto3";
|
||||
|
||||
package domi.tensorflow;
|
||||
|
||||
import "graph.proto";
|
||||
|
||||
message GeGraphDef {
|
||||
string name = 1;
|
||||
GraphDef graph = 2;
|
||||
}
|
||||
|
||||
message GraphDefLibrary {
|
||||
repeated GeGraphDef graph_def = 1;
|
||||
};
|
||||
@ -0,0 +1,63 @@
|
||||
syntax = "proto3";
|
||||
|
||||
package domi.tensorflow;
|
||||
option cc_enable_arenas = true;
|
||||
option java_outer_classname = "NodeProto";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "org.tensorflow.framework";
|
||||
|
||||
import "attr_value.proto";
|
||||
|
||||
message NodeDef {
|
||||
// The name given to this operator. Used for naming inputs,
|
||||
// logging, visualization, etc. Unique within a single GraphDef.
|
||||
// Must match the regexp "[A-Za-z0-9.][A-Za-z0-9_./]*".
|
||||
string name = 1;
|
||||
|
||||
// The operation name. There may be custom parameters in attrs.
|
||||
// Op names starting with an underscore are reserved for internal use.
|
||||
string op = 2;
|
||||
|
||||
// Each input is "node:src_output" with "node" being a string name and
|
||||
// "src_output" indicating which output tensor to use from "node". If
|
||||
// "src_output" is 0 the ":0" suffix can be omitted. Regular inputs
|
||||
// may optionally be followed by control inputs that have the format
|
||||
// "^node".
|
||||
repeated string input = 3;
|
||||
|
||||
// A (possibly partial) specification for the device on which this
|
||||
// node should be placed.
|
||||
// The expected syntax for this string is as follows:
|
||||
//
|
||||
// DEVICE_SPEC ::= PARTIAL_SPEC
|
||||
//
|
||||
// PARTIAL_SPEC ::= ("/" CONSTRAINT) *
|
||||
// CONSTRAINT ::= ("job:" JOB_NAME)
|
||||
// | ("replica:" [1-9][0-9]*)
|
||||
// | ("task:" [1-9][0-9]*)
|
||||
// | ("device:" [A-Za-z]* ":" ([1-9][0-9]* | "*") )
|
||||
//
|
||||
// Valid values for this string include:
|
||||
// * "/job:worker/replica:0/task:1/device:GPU:3" (full specification)
|
||||
// * "/job:worker/device:GPU:3" (partial specification)
|
||||
// * "" (no specification)
|
||||
//
|
||||
// If the constraints do not resolve to a single device (or if this
|
||||
// field is empty or not present), the runtime will attempt to
|
||||
// choose a device automatically.
|
||||
string device = 4;
|
||||
|
||||
// Operation-specific graph-construction-time configuration.
|
||||
// Note that this should include all attrs defined in the
|
||||
// corresponding OpDef, including those with a value matching
|
||||
// the default -- this allows the default to change and makes
|
||||
// NodeDefs easier to interpret on their own. However, if
|
||||
// an attr with a default is not specified in this list, the
|
||||
// default will be used.
|
||||
// The "names" (keys) must match the regexp "[a-z][a-z0-9_]+" (and
|
||||
// one of the names from the corresponding OpDef's attr field).
|
||||
// The values must have a type matching the corresponding OpDef
|
||||
// attr's type field.
|
||||
// Add some examples here showing best practices.
|
||||
map<string, AttrValue> attr = 5;
|
||||
};
|
||||
@ -0,0 +1,164 @@
|
||||
syntax = "proto3";
|
||||
|
||||
package domi.tensorflow;
|
||||
option cc_enable_arenas = true;
|
||||
option java_outer_classname = "OpDefProtos";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "org.tensorflow.framework";
|
||||
|
||||
import "attr_value.proto";
|
||||
import "types.proto";
|
||||
|
||||
// Defines an operation. A NodeDef in a GraphDef specifies an Op by
|
||||
// using the "op" field which should match the name of a OpDef.
|
||||
// LINT.IfChange
|
||||
message OpDef {
|
||||
// Op names starting with an underscore are reserved for internal use.
|
||||
// Names should be CamelCase and match the regexp "[A-Z][a-zA-Z0-9_]*".
|
||||
string name = 1;
|
||||
|
||||
// For describing inputs and outputs.
|
||||
message ArgDef {
|
||||
// Name for the input/output. Should match the regexp "[a-z][a-z0-9_]*".
|
||||
string name = 1;
|
||||
|
||||
// Human readable description.
|
||||
string description = 2;
|
||||
|
||||
// Describes the type of one or more tensors that are accepted/produced
|
||||
// by this input/output arg. The only legal combinations are:
|
||||
// * For a single tensor: either the "type" field is set or the
|
||||
// "type_attr" field is set to the name of an attr with type "type".
|
||||
// * For a sequence of tensors with the same type: the "number_attr"
|
||||
// field will be set to the name of an attr with type "int", and
|
||||
// either the "type" or "type_attr" field will be set as for
|
||||
// single tensors.
|
||||
// * For a sequence of tensors, the "type_list_attr" field will be set
|
||||
// to the name of an attr with type "list(type)".
|
||||
DataType type = 3;
|
||||
string type_attr = 4; // if specified, attr must have type "type"
|
||||
string number_attr = 5; // if specified, attr must have type "int"
|
||||
// If specified, attr must have type "list(type)", and none of
|
||||
// type, type_attr, and number_attr may be specified.
|
||||
string type_list_attr = 6;
|
||||
|
||||
// For inputs: if true, the inputs are required to be refs.
|
||||
// By default, inputs can be either refs or non-refs.
|
||||
// For outputs: if true, outputs are refs, otherwise they are not.
|
||||
bool is_ref = 16;
|
||||
};
|
||||
|
||||
// Description of the input(s).
|
||||
repeated ArgDef input_arg = 2;
|
||||
|
||||
// Description of the output(s).
|
||||
repeated ArgDef output_arg = 3;
|
||||
|
||||
// Description of the graph-construction-time configuration of this
|
||||
// Op. That is to say, this describes the attr fields that will
|
||||
// be specified in the NodeDef.
|
||||
message AttrDef {
|
||||
// A descriptive name for the argument. May be used, e.g. by the
|
||||
// Python client, as a keyword argument name, and so should match
|
||||
// the regexp "[a-z][a-z0-9_]+".
|
||||
string name = 1;
|
||||
|
||||
// One of the type names from attr_value.proto ("string", "list(string)",
|
||||
// "int", etc.).
|
||||
string type = 2;
|
||||
|
||||
// A reasonable default for this attribute if the user does not supply
|
||||
// a value. If not specified, the user must supply a value.
|
||||
AttrValue default_value = 3;
|
||||
|
||||
// Human-readable description.
|
||||
string description = 4;
|
||||
|
||||
|
||||
// --- Constraints ---
|
||||
// These constraints are only in effect if specified. Default is no
|
||||
// constraints.
|
||||
|
||||
// For type == "int", this is a minimum value. For "list(___)"
|
||||
// types, this is the minimum length.
|
||||
bool has_minimum = 5;
|
||||
int64 minimum = 6;
|
||||
|
||||
// The set of allowed values. Has type that is the "list" version
|
||||
// of the "type" field above (uses the "list" field of AttrValue).
|
||||
// If type == "type" or "list(type)" above, then the "type" field
|
||||
// of "allowed_values.list" has the set of allowed DataTypes.
|
||||
// If type == "string" or "list(string)", then the "s" field of
|
||||
// "allowed_values.list" has the set of allowed strings.
|
||||
AttrValue allowed_values = 7;
|
||||
}
|
||||
repeated AttrDef attr = 4;
|
||||
|
||||
// Optional deprecation based on GraphDef versions.
|
||||
OpDeprecation deprecation = 8;
|
||||
|
||||
// One-line human-readable description of what the Op does.
|
||||
string summary = 5;
|
||||
|
||||
// Additional, longer human-readable description of what the Op does.
|
||||
string description = 6;
|
||||
|
||||
// -------------------------------------------------------------------------
|
||||
// Which optimizations this operation can participate in.
|
||||
|
||||
// True if the operation is commutative ("op(a,b) == op(b,a)" for all inputs)
|
||||
bool is_commutative = 18;
|
||||
|
||||
// If is_aggregate is true, then this operation accepts N >= 2
|
||||
// inputs and produces 1 output all of the same type. Should be
|
||||
// associative and commutative, and produce output with the same
|
||||
// shape as the input. The optimizer may replace an aggregate op
|
||||
// taking input from multiple devices with a tree of aggregate ops
|
||||
// that aggregate locally within each device (and possibly within
|
||||
// groups of nearby devices) before communicating.
|
||||
bool is_aggregate = 16; // for things like add
|
||||
|
||||
// Other optimizations go here, like
|
||||
// can_alias_input, rewrite_when_output_unused, partitioning_strategy, etc.
|
||||
|
||||
// -------------------------------------------------------------------------
|
||||
// Optimization constraints.
|
||||
|
||||
// Ops are marked as stateful if their behavior depends on some state beyond
|
||||
// their input tensors (e.g. variable reading op) or if they have
|
||||
// a side-effect (e.g. printing or asserting ops). Equivalently, stateless ops
|
||||
// must always produce the same output for the same input and have
|
||||
// no side-effects.
|
||||
//
|
||||
// By default Ops may be moved between devices. Stateful ops should
|
||||
// either not be moved, or should only be moved if that state can also
|
||||
// be moved (e.g. via some sort of save / restore).
|
||||
// Stateful ops are guaranteed to never be optimized away by Common
|
||||
// Subexpression Elimination (CSE).
|
||||
bool is_stateful = 17; // for things like variables, queue
|
||||
|
||||
// -------------------------------------------------------------------------
|
||||
// Non-standard options.
|
||||
|
||||
// By default, all inputs to an Op must be initialized Tensors. Ops
|
||||
// that may initialize tensors for the first time should set this
|
||||
// field to true, to allow the Op to take an uninitialized Tensor as
|
||||
// input.
|
||||
bool allows_uninitialized_input = 19; // for Assign, etc.
|
||||
};
|
||||
// LINT.ThenChange(
|
||||
// https://www.tensorflow.org/code/tensorflow/core/framework/op_def_util.cc)
|
||||
|
||||
// Information about version-dependent deprecation of an op
|
||||
message OpDeprecation {
|
||||
// First GraphDef version at which the op is disallowed.
|
||||
int32 version = 1;
|
||||
|
||||
// Explanation of why it was deprecated and what to use instead.
|
||||
string explanation = 2;
|
||||
};
|
||||
|
||||
// A collection of OpDefs
|
||||
message OpList {
|
||||
repeated OpDef op = 1;
|
||||
};
|
||||
@ -0,0 +1,29 @@
|
||||
syntax = "proto3";
|
||||
|
||||
package domi.tensorflow;
|
||||
option cc_enable_arenas = true;
|
||||
option java_outer_classname = "ResourceHandle";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "org.tensorflow.framework";
|
||||
|
||||
// Protocol buffer representing a handle to a tensorflow resource. Handles are
|
||||
// not valid across executions, but can be serialized back and forth from within
|
||||
// a single run.
|
||||
message ResourceHandleProto {
|
||||
// Unique name for the device containing the resource.
|
||||
string device = 1;
|
||||
|
||||
// Container in which this resource is placed.
|
||||
string container = 2;
|
||||
|
||||
// Unique name of this resource.
|
||||
string name = 3;
|
||||
|
||||
// Hash code for the type of the resource. Is only valid in the same device
|
||||
// and in the same execution.
|
||||
uint64 hash_code = 4;
|
||||
|
||||
// For debug-only, the name of the type pointed to by this handle, if
|
||||
// available.
|
||||
string maybe_type_name = 5;
|
||||
};
|
||||
@ -0,0 +1,94 @@
|
||||
syntax = "proto3";
|
||||
|
||||
package domi.tensorflow;
|
||||
option cc_enable_arenas = true;
|
||||
option java_outer_classname = "TensorProtos";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "org.tensorflow.framework";
|
||||
|
||||
import "resource_handle.proto";
|
||||
import "tensor_shape.proto";
|
||||
import "types.proto";
|
||||
|
||||
// Protocol buffer representing a tensor.
|
||||
message TensorProto {
|
||||
DataType dtype = 1;
|
||||
|
||||
// Shape of the tensor.
|
||||
TensorShapeProto tensor_shape = 2;
|
||||
|
||||
// Only one of the representations below is set, one of "tensor_contents" and
|
||||
// the "xxx_val" attributes. We are not using oneof because as oneofs cannot
|
||||
// contain repeated fields it would require another extra set of messages.
|
||||
|
||||
// Version number.
|
||||
//
|
||||
// In version 0, if the "repeated xxx" representations contain only one
|
||||
// element, that element is repeated to fill the shape. This makes it easy
|
||||
// to represent a constant Tensor with a single value.
|
||||
int32 version_number = 3;
|
||||
|
||||
// Serialized raw tensor content from either Tensor::AsProtoTensorContent or
|
||||
// memcpy in tensorflow::grpc::EncodeTensorToByteBuffer. This representation
|
||||
// can be used for all tensor types. The purpose of this representation is to
|
||||
// reduce serialization overhead during RPC call by avoiding serialization of
|
||||
// many repeated small items.
|
||||
bytes tensor_content = 4;
|
||||
|
||||
// Type specific representations that make it easy to create tensor protos in
|
||||
// all languages. Only the representation corresponding to "dtype" can
|
||||
// be set. The values hold the flattened representation of the tensor in
|
||||
// row major order.
|
||||
|
||||
// DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll
|
||||
// have some pointless zero padding for each value here.
|
||||
repeated int32 half_val = 13 [packed = true];
|
||||
|
||||
// DT_FLOAT.
|
||||
repeated float float_val = 5 [packed = true];
|
||||
|
||||
// DT_DOUBLE.
|
||||
repeated double double_val = 6 [packed = true];
|
||||
|
||||
// DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
|
||||
repeated int32 int_val = 7 [packed = true];
|
||||
|
||||
// DT_STRING
|
||||
repeated bytes string_val = 8;
|
||||
|
||||
// DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real
|
||||
// and imaginary parts of i-th single precision complex.
|
||||
repeated float scomplex_val = 9 [packed = true];
|
||||
|
||||
// DT_INT64
|
||||
repeated int64 int64_val = 10 [packed = true];
|
||||
|
||||
// DT_BOOL
|
||||
repeated bool bool_val = 11 [packed = true];
|
||||
|
||||
// DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real
|
||||
// and imaginary parts of i-th double precision complex.
|
||||
repeated double dcomplex_val = 12 [packed = true];
|
||||
|
||||
// DT_RESOURCE
|
||||
repeated ResourceHandleProto resource_handle_val = 14;
|
||||
|
||||
// DT_VARIANT
|
||||
repeated VariantTensorDataProto variant_val = 15;
|
||||
|
||||
// DT_UINT32
|
||||
repeated uint32 uint32_val = 16 [packed = true];
|
||||
|
||||
// DT_UINT64
|
||||
repeated uint64 uint64_val = 17 [packed = true];
|
||||
};
|
||||
|
||||
// Protocol buffer representing the serialization format of DT_VARIANT tensors.
|
||||
message VariantTensorDataProto {
|
||||
// Name of the type of objects being serialized.
|
||||
string type_name = 1;
|
||||
// Portions of the object that are not Tensors.
|
||||
bytes metadata = 2;
|
||||
// Tensors contained within objects being serialized.
|
||||
repeated TensorProto tensors = 3;
|
||||
}
|
||||
@ -0,0 +1,45 @@
|
||||
// Protocol buffer representing the shape of tensors.
|
||||
|
||||
syntax = "proto3";
|
||||
option cc_enable_arenas = true;
|
||||
option java_outer_classname = "TensorShapeProtos";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "org.tensorflow.framework";
|
||||
|
||||
package domi.tensorflow;
|
||||
|
||||
// Dimensions of a tensor.
|
||||
message TensorShapeProto {
|
||||
// One dimension of the tensor.
|
||||
message Dim {
|
||||
// Size of the tensor in that dimension.
|
||||
// This value must be >= -1, but values of -1 are reserved for "unknown"
|
||||
// shapes (values of -1 mean "unknown" dimension). Certain wrappers
|
||||
// that work with TensorShapeProto may fail at runtime when deserializing
|
||||
// a TensorShapeProto containing a dim value of -1.
|
||||
int64 size = 1;
|
||||
|
||||
// Optional name of the tensor dimension.
|
||||
string name = 2;
|
||||
};
|
||||
|
||||
// Dimensions of the tensor, such as {"input", 30}, {"output", 40}
|
||||
// for a 30 x 40 2D tensor. If an entry has size -1, this
|
||||
// corresponds to a dimension of unknown size. The names are
|
||||
// optional.
|
||||
//
|
||||
// The order of entries in "dim" matters: It indicates the layout of the
|
||||
// values in the tensor in-memory representation.
|
||||
//
|
||||
// The first entry in "dim" is the outermost dimension used to layout the
|
||||
// values, the last entry is the innermost dimension. This matches the
|
||||
// in-memory layout of RowMajor Eigen tensors.
|
||||
//
|
||||
// If "dim.size()" > 0, "unknown_rank" must be false.
|
||||
repeated Dim dim = 2;
|
||||
|
||||
// If true, the number of dimensions in the shape is unknown.
|
||||
//
|
||||
// If true, "dim.size()" must be 0.
|
||||
bool unknown_rank = 3;
|
||||
};
|
||||
@ -0,0 +1,74 @@
|
||||
syntax = "proto3";
|
||||
|
||||
package domi.tensorflow;
|
||||
option cc_enable_arenas = true;
|
||||
option java_outer_classname = "TypesProtos";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "org.tensorflow.framework";
|
||||
|
||||
// LINT.IfChange
|
||||
enum DataType {
|
||||
// Not a legal value for DataType. Used to indicate a DataType field
|
||||
// has not been set.
|
||||
DT_INVALID = 0;
|
||||
|
||||
// Data types that all computation devices are expected to be
|
||||
// capable to support.
|
||||
DT_FLOAT = 1;
|
||||
DT_DOUBLE = 2;
|
||||
DT_INT32 = 3;
|
||||
DT_UINT8 = 4;
|
||||
DT_INT16 = 5;
|
||||
DT_INT8 = 6;
|
||||
DT_STRING = 7;
|
||||
DT_COMPLEX64 = 8; // Single-precision complex
|
||||
DT_INT64 = 9;
|
||||
DT_BOOL = 10;
|
||||
DT_QINT8 = 11; // Quantized int8
|
||||
DT_QUINT8 = 12; // Quantized uint8
|
||||
DT_QINT32 = 13; // Quantized int32
|
||||
DT_BFLOAT16 = 14; // Float32 truncated to 16 bits. Only for cast ops.
|
||||
DT_QINT16 = 15; // Quantized int16
|
||||
DT_QUINT16 = 16; // Quantized uint16
|
||||
DT_UINT16 = 17;
|
||||
DT_COMPLEX128 = 18; // Double-precision complex
|
||||
DT_HALF = 19;
|
||||
DT_RESOURCE = 20;
|
||||
DT_VARIANT = 21; // Arbitrary C++ data types
|
||||
DT_UINT32 = 22;
|
||||
DT_UINT64 = 23;
|
||||
|
||||
// Do not use! These are only for parameters. Every enum above
|
||||
// should have a corresponding value below (verified by types_test).
|
||||
DT_FLOAT_REF = 101;
|
||||
DT_DOUBLE_REF = 102;
|
||||
DT_INT32_REF = 103;
|
||||
DT_UINT8_REF = 104;
|
||||
DT_INT16_REF = 105;
|
||||
DT_INT8_REF = 106;
|
||||
DT_STRING_REF = 107;
|
||||
DT_COMPLEX64_REF = 108;
|
||||
DT_INT64_REF = 109;
|
||||
DT_BOOL_REF = 110;
|
||||
DT_QINT8_REF = 111;
|
||||
DT_QUINT8_REF = 112;
|
||||
DT_QINT32_REF = 113;
|
||||
DT_BFLOAT16_REF = 114;
|
||||
DT_QINT16_REF = 115;
|
||||
DT_QUINT16_REF = 116;
|
||||
DT_UINT16_REF = 117;
|
||||
DT_COMPLEX128_REF = 118;
|
||||
DT_HALF_REF = 119;
|
||||
DT_RESOURCE_REF = 120;
|
||||
DT_VARIANT_REF = 121;
|
||||
DT_UINT32_REF = 122;
|
||||
DT_UINT64_REF = 123;
|
||||
}
|
||||
// LINT.ThenChange(
|
||||
// https://www.tensorflow.org/code/tensorflow/c/c_api.h,
|
||||
// https://www.tensorflow.org/code/tensorflow/go/tensor.go,
|
||||
// https://www.tensorflow.org/code/tensorflow/core/framework/tensor.cc,
|
||||
// https://www.tensorflow.org/code/tensorflow/core/framework/types.h,
|
||||
// https://www.tensorflow.org/code/tensorflow/core/framework/types.cc,
|
||||
// https://www.tensorflow.org/code/tensorflow/python/framework/dtypes.py,
|
||||
// https://www.tensorflow.org/code/tensorflow/python/framework/function.py)
|
||||
@ -0,0 +1,31 @@
|
||||
syntax = "proto3";
|
||||
|
||||
package domi.tensorflow;
|
||||
option cc_enable_arenas = true;
|
||||
option java_outer_classname = "VersionsProtos";
|
||||
option java_multiple_files = true;
|
||||
option java_package = "org.tensorflow.framework";
|
||||
|
||||
// Version information for a piece of serialized data
|
||||
//
|
||||
// There are different types of versions for each type of data
|
||||
// (GraphDef, etc.), but they all have the same common shape
|
||||
// described here.
|
||||
//
|
||||
// Each consumer has "consumer" and "min_producer" versions (specified
|
||||
// elsewhere). A consumer is allowed to consume this data if
|
||||
//
|
||||
// producer >= min_producer
|
||||
// consumer >= min_consumer
|
||||
// consumer not in bad_consumers
|
||||
//
|
||||
message VersionDef {
|
||||
// The version of the code that produced this data.
|
||||
int32 producer = 1;
|
||||
|
||||
// Any consumer below this version is not allowed to consume this data.
|
||||
int32 min_consumer = 2;
|
||||
|
||||
// Specific consumer versions which are disallowed (e.g. due to bugs).
|
||||
repeated int32 bad_consumers = 3;
|
||||
};
|
||||
@ -0,0 +1,111 @@
|
||||
syntax = "proto3";
|
||||
package toolkit.dumpdata;
|
||||
|
||||
enum OutputDataType {
|
||||
DT_UNDEFINED = 0;
|
||||
DT_FLOAT = 1;
|
||||
DT_FLOAT16 = 2;
|
||||
DT_INT8 = 3;
|
||||
DT_UINT8 = 4;
|
||||
DT_INT16 = 5;
|
||||
DT_UINT16 = 6;
|
||||
DT_INT32 = 7;
|
||||
DT_INT64 = 8;
|
||||
DT_UINT32 = 9;
|
||||
DT_UINT64 = 10;
|
||||
DT_BOOL = 11;
|
||||
DT_DOUBLE = 12;
|
||||
DT_STRING = 13;
|
||||
DT_DUAL_SUB_INT8 = 14;
|
||||
DT_DUAL_SUB_UINT8 = 15;
|
||||
DT_COMPLEX64 = 16;
|
||||
DT_COMPLEX128 = 17;
|
||||
DT_QINT8 = 18;
|
||||
DT_QINT16 = 19;
|
||||
DT_QINT32 = 20;
|
||||
DT_QUINT8 = 21;
|
||||
DT_QUINT16 = 22;
|
||||
DT_RESOURCE = 23;
|
||||
DT_STRING_REF = 24;
|
||||
DT_DUAL = 25;
|
||||
}
|
||||
|
||||
enum OutputFormat {
|
||||
FORMAT_NCHW = 0;
|
||||
FORMAT_NHWC = 1;
|
||||
FORMAT_ND = 2;
|
||||
FORMAT_NC1HWC0 = 3;
|
||||
FORMAT_FRACTAL_Z = 4;
|
||||
FORMAT_NC1C0HWPAD = 5;
|
||||
FORMAT_NHWC1C0 = 6;
|
||||
FORMAT_FSR_NCHW = 7;
|
||||
FORMAT_FRACTAL_DECONV = 8;
|
||||
FORMAT_C1HWNC0 = 9;
|
||||
FORMAT_FRACTAL_DECONV_TRANSPOSE = 10;
|
||||
FORMAT_FRACTAL_DECONV_SP_STRIDE_TRANS = 11;
|
||||
FORMAT_NC1HWC0_C04 = 12;
|
||||
FORMAT_FRACTAL_Z_C04 = 13;
|
||||
FORMAT_CHWN = 14;
|
||||
FORMAT_FRACTAL_DECONV_SP_STRIDE8_TRANS = 15;
|
||||
FORMAT_HWCN = 16;
|
||||
FORMAT_NC1KHKWHWC0 = 17;
|
||||
FORMAT_BN_WEIGHT = 18;
|
||||
FORMAT_FILTER_HWCK = 19;
|
||||
FORMAT_HASHTABLE_LOOKUP_LOOKUPS=20;
|
||||
FORMAT_HASHTABLE_LOOKUP_KEYS = 21;
|
||||
FORMAT_HASHTABLE_LOOKUP_VALUE = 22;
|
||||
FORMAT_HASHTABLE_LOOKUP_OUTPUT = 23;
|
||||
FORMAT_HASHTABLE_LOOKUP_HITS=24;
|
||||
FORMAT_C1HWNCoC0 = 25;
|
||||
FORMAT_MD = 26;
|
||||
FORMAT_NDHWC = 27;
|
||||
FORMAT_FRACTAL_ZZ = 28;
|
||||
FORMAT_FRACTAL_NZ = 29;
|
||||
FORMAT_RESERVED = 30;
|
||||
}
|
||||
|
||||
message OriginalOp {
|
||||
string name = 1;
|
||||
uint32 output_index = 2;
|
||||
OutputDataType data_type = 3;
|
||||
OutputFormat format = 4;
|
||||
}
|
||||
|
||||
message Shape {
|
||||
repeated uint64 dim = 1;
|
||||
}
|
||||
|
||||
message OpOutput {
|
||||
OutputDataType data_type = 1;
|
||||
OutputFormat format = 2;
|
||||
Shape shape = 3;
|
||||
OriginalOp original_op = 4; // the original op corresponding to the output
|
||||
bytes data = 5;
|
||||
uint64 size = 6;
|
||||
}
|
||||
|
||||
message OpInput {
|
||||
OutputDataType data_type = 1;
|
||||
OutputFormat format = 2;
|
||||
Shape shape = 3;
|
||||
bytes data = 4;
|
||||
uint64 size = 5;
|
||||
}
|
||||
|
||||
enum BufferType {
|
||||
L1 = 0;
|
||||
}
|
||||
|
||||
message OpBuffer {
|
||||
BufferType buffer_type = 1;
|
||||
bytes data = 2;
|
||||
uint64 size = 3;
|
||||
}
|
||||
|
||||
message DumpData{
|
||||
string version = 1;
|
||||
uint64 dump_time = 2;
|
||||
repeated OpOutput output = 3;
|
||||
repeated OpInput input = 4;
|
||||
repeated OpBuffer buffer = 5;
|
||||
}
|
||||
File diff suppressed because it is too large
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Reference in new issue