add op version checker to ir passes (#27329)
Shang Zhizhou
4 years ago
committed by
GitHub
parent
515efe4240
commit
3c11717988
@ -0,0 +1,171 @@
|
||||
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
|
||||
#
|
||||
# Licensed under the Apache License, Version 2.0 (the "License");
|
||||
# you may not use this file except in compliance with the License.
|
||||
# You may obtain a copy of the License at
|
||||
#
|
||||
# http://www.apache.org/licenses/LICENSE-2.0
|
||||
#
|
||||
# Unless required by applicable law or agreed to in writing, software
|
||||
# distributed under the License is distributed on an "AS IS" BASIS,
|
||||
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
# See the License for the specific language governing permissions and
|
||||
# limitations under the License.
|
||||
|
||||
from __future__ import print_function
|
||||
|
||||
import unittest
|
||||
import numpy as np
|
||||
from inference_pass_test import InferencePassTest
|
||||
import paddle.fluid as fluid
|
||||
import paddle.fluid.core as core
|
||||
from paddle.fluid.core import AnalysisConfig
|
||||
"""Test for fusion of conv and bias."""
|
||||
|
||||
|
||||
#padding SAME
|
||||
class ConvBiasMkldnnFusePassTest(InferencePassTest):
|
||||
def setUp(self):
|
||||
with fluid.program_guard(self.main_program, self.startup_program):
|
||||
data = fluid.data(
|
||||
name="data", shape=[-1, 3, 100, 100], dtype="float32")
|
||||
param_attr = fluid.ParamAttr(
|
||||
initializer=fluid.initializer.Xavier(uniform=False),
|
||||
learning_rate=0.001)
|
||||
conv_out = fluid.layers.conv2d(
|
||||
input=data,
|
||||
num_filters=3,
|
||||
filter_size=3,
|
||||
padding="SAME",
|
||||
bias_attr=param_attr)
|
||||
|
||||
self.feeds = {
|
||||
"data": np.random.random((1, 3, 100, 100)).astype("float32")
|
||||
}
|
||||
self.fetch_list = [conv_out]
|
||||
self.enable_mkldnn = True
|
||||
|
||||
def test_check_output(self):
|
||||
use_gpu = False
|
||||
self.check_output_with_option(use_gpu)
|
||||
|
||||
|
||||
#padding VALID
|
||||
class ConvBiasMkldnnFusePassTest1(InferencePassTest):
|
||||
def setUp(self):
|
||||
with fluid.program_guard(self.main_program, self.startup_program):
|
||||
data = fluid.data(
|
||||
name="data", shape=[-1, 3, 100, 100], dtype="float32")
|
||||
param_attr = fluid.ParamAttr(
|
||||
initializer=fluid.initializer.Xavier(uniform=False),
|
||||
learning_rate=0.001)
|
||||
conv_out = fluid.layers.conv2d(
|
||||
input=data,
|
||||
num_filters=3,
|
||||
filter_size=3,
|
||||
padding="VALID",
|
||||
bias_attr=param_attr)
|
||||
|
||||
self.feeds = {
|
||||
"data": np.random.random((1, 3, 100, 100)).astype("float32")
|
||||
}
|
||||
self.fetch_list = [conv_out]
|
||||
self.enable_mkldnn = True
|
||||
|
||||
def test_check_output(self):
|
||||
use_gpu = False
|
||||
self.check_output_with_option(use_gpu)
|
||||
|
||||
|
||||
#padding number
|
||||
class ConvBiasMkldnnFusePassTest2(InferencePassTest):
|
||||
def setUp(self):
|
||||
with fluid.program_guard(self.main_program, self.startup_program):
|
||||
data = fluid.data(
|
||||
name="data", shape=[-1, 3, 100, 100], dtype="float32")
|
||||
param_attr = fluid.ParamAttr(
|
||||
initializer=fluid.initializer.Xavier(uniform=False),
|
||||
learning_rate=0.001)
|
||||
conv_out = fluid.layers.conv2d(
|
||||
input=data,
|
||||
num_filters=3,
|
||||
filter_size=3,
|
||||
padding=[2, 4, 6, 8],
|
||||
bias_attr=param_attr)
|
||||
|
||||
self.feeds = {
|
||||
"data": np.random.random((1, 3, 100, 100)).astype("float32")
|
||||
}
|
||||
self.fetch_list = [conv_out]
|
||||
self.enable_mkldnn = True
|
||||
|
||||
def test_check_output(self):
|
||||
use_gpu = False
|
||||
self.check_output_with_option(use_gpu)
|
||||
|
||||
|
||||
#dilation not supported yet, just print warning log and does not fuse
|
||||
class ConvBiasMkldnnFusePassTest3(InferencePassTest):
|
||||
def setUp(self):
|
||||
with fluid.program_guard(self.main_program, self.startup_program):
|
||||
data = fluid.data(
|
||||
name="data", shape=[-1, 3, 100, 100], dtype="float32")
|
||||
param_attr = fluid.ParamAttr(
|
||||
initializer=fluid.initializer.Xavier(uniform=False),
|
||||
learning_rate=0.001)
|
||||
conv_out = fluid.layers.conv2d(
|
||||
input=data,
|
||||
num_filters=3,
|
||||
filter_size=3,
|
||||
padding="VALID",
|
||||
dilation=2,
|
||||
groups=3,
|
||||
bias_attr=param_attr,
|
||||
use_cudnn=False,
|
||||
act="softmax",
|
||||
data_format="NCHW")
|
||||
|
||||
self.feeds = {
|
||||
"data": np.random.random((1, 3, 100, 100)).astype("float32")
|
||||
}
|
||||
self.fetch_list = [conv_out]
|
||||
self.enable_mkldnn = True
|
||||
|
||||
def test_check_output(self):
|
||||
use_gpu = False
|
||||
self.check_output_with_option(use_gpu)
|
||||
|
||||
|
||||
#all conv params except for dilation
|
||||
class ConvBiasMkldnnFusePassTest4(InferencePassTest):
|
||||
def setUp(self):
|
||||
with fluid.program_guard(self.main_program, self.startup_program):
|
||||
data = fluid.data(
|
||||
name="data", shape=[-1, 3, 100, 100], dtype="float32")
|
||||
param_attr = fluid.ParamAttr(
|
||||
initializer=fluid.initializer.Xavier(uniform=False),
|
||||
learning_rate=0.001)
|
||||
conv_out = fluid.layers.conv2d(
|
||||
input=data,
|
||||
num_filters=3,
|
||||
filter_size=3,
|
||||
padding="VALID",
|
||||
groups=3,
|
||||
bias_attr=param_attr,
|
||||
use_cudnn=False,
|
||||
act="softmax",
|
||||
data_format="NCHW")
|
||||
|
||||
self.feeds = {
|
||||
"data": np.random.random((1, 3, 100, 100)).astype("float32")
|
||||
}
|
||||
self.fetch_list = [conv_out]
|
||||
self.enable_mkldnn = True
|
||||
|
||||
def test_check_output(self):
|
||||
use_gpu = False
|
||||
self.check_output_with_option(use_gpu)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
unittest.main()
|
||||
Loading…
Reference in new issue