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105 lines
3.5 KiB
105 lines
3.5 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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from collections import OrderedDict
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from ..framework import Program
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__all__ = ['op_freq_statistic']
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def op_freq_statistic(program):
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"""
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Statistics of Op frequency.
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Args:
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program(Program): The current Program.
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Returns:
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uni_op_freq(dict): the single op frequency.
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adj_2_op_freq(dict): the two adjacent ops frequency.
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Examples:
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>>> import paddle.fluid as fluid
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>>> uni_op_freq, adj_2_op_freq = fluid.contrib.op_freq_statistic(
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>>> fluid.default_main_program())
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>>> for op_type, op_num in uni_op_freq:
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>>> print("%s \t %d" % (op_type, op_num))
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>>> for op_type, op_num in adj_2_op_freq:
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>>> print("%s \t %d" % (op_type, op_num))
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"""
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if not isinstance(program, Program):
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raise TypeError("The input type should be Porgram."
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"But you passed in %s" % (type(program)))
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uni_op_freq = OrderedDict()
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adj_2_op_freq = OrderedDict()
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op_in_ops = OrderedDict()
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parameters = [p.name for p in program.blocks[0].all_parameters()]
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# get uni_op_freq
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for op in program.global_block().ops:
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had_recorded = False
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for var_name in op.output_arg_names:
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if var_name in parameters:
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continue
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if not had_recorded and uni_op_freq.has_key(op.type):
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uni_op_freq[op.type] += 1
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had_recorded = True
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elif not had_recorded:
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uni_op_freq[op.type] = 1
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had_recorded = True
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# get adj_2_op_freq
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var_gen_op = {}
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for op in program.global_block().ops:
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for var_name in op.input_arg_names:
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if var_name in parameters:
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continue
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if var_gen_op.has_key(var_name):
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assert len(var_gen_op[var_name]) > 0
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if op_in_ops.has_key(op.type):
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op_in_ops[op.type].append(var_gen_op[var_name][-1])
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else:
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op_in_ops[op.type] = [var_gen_op[var_name][-1]]
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else:
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print("Var's generate op is not found,%s, %s" %
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(var_name, op.type))
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for var_name in op.output_arg_names:
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if var_gen_op.has_key(var_name):
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var_gen_op[var_name].append(op.type)
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else:
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var_gen_op[var_name] = [op.type]
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for op, in_ops in op_in_ops.iteritems():
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for in_op in in_ops:
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op_op = in_op + "->" + op
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if adj_2_op_freq.has_key(op_op):
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adj_2_op_freq[op_op] += 1
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else:
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adj_2_op_freq[op_op] = 1
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uni_op_freq = sorted(
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uni_op_freq.items(), key=lambda item: item[1], reverse=True)
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adj_2_op_freq = sorted(
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adj_2_op_freq.items(), key=lambda item: item[1], reverse=True)
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return uni_op_freq, adj_2_op_freq
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