未验证 提交 1db61c3e 编写于 作者: B baoachun 提交者: GitHub

add mul_lstm_fuse_pass ut (#37795)

* add mul_lstm_fuse_pass ut

* update mul_lstm_fuse_pass ut

* update ut

* update ut

* update ut

* add CPU ut cmake setting

* update ut
上级 ee5f3641
...@@ -68,13 +68,13 @@ MulLstmFusePass::MulLstmFusePass() { ...@@ -68,13 +68,13 @@ MulLstmFusePass::MulLstmFusePass() {
.IsType<bool>() .IsType<bool>()
.End() .End()
.AddAttr("gate_activation") .AddAttr("gate_activation")
.IsStringIn({"sigmoid", "tanh", "relu", "identity"}) .IsStringIn({"sigmoid"})
.End() .End()
.AddAttr("cell_activation") .AddAttr("cell_activation")
.IsStringIn({"sigmoid", "tanh", "relu", "identity"}) .IsStringIn({"tanh", "relu", "identity"})
.End() .End()
.AddAttr("candidate_activation") .AddAttr("candidate_activation")
.IsStringIn({"sigmoid", "tanh", "relu", "identity"}) .IsStringIn({"tanh", "relu", "identity"})
.End(); .End();
AddOpCompat(OpCompat("mul")) AddOpCompat(OpCompat("mul"))
.AddInput("X") .AddInput("X")
......
...@@ -7,6 +7,13 @@ string(REPLACE ".py" "" TEST_TRT_IR_PASSES "${TEST_TRT_IR_PASSES}") ...@@ -7,6 +7,13 @@ string(REPLACE ".py" "" TEST_TRT_IR_PASSES "${TEST_TRT_IR_PASSES}")
file(GLOB TEST_TRT_CONVERTER RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_trt_convert_*.py") file(GLOB TEST_TRT_CONVERTER RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_trt_convert_*.py")
string(REPLACE ".py" "" TEST_TRT_CONVERTER "${TEST_TRT_CONVERTER}") string(REPLACE ".py" "" TEST_TRT_CONVERTER "${TEST_TRT_CONVERTER}")
# Only for cpu(mkl + openblas)
set(TEST_INFERENCE_CPU_UT "test_mul_lstm_fuse_pass")
foreach(CPU_UT ${TEST_INFERENCE_CPU_UT})
list(REMOVE_ITEM TEST_INFERENCE_IR_PASSES ${CPU_UT})
endforeach()
foreach(TEST_INFERENCE_IR_PASS ${TEST_TRT_IR_PASSES}) foreach(TEST_INFERENCE_IR_PASS ${TEST_TRT_IR_PASSES})
list(REMOVE_ITEM TEST_INFERENCE_IR_PASSES ${TEST_INFERENCE_IR_PASS}) list(REMOVE_ITEM TEST_INFERENCE_IR_PASSES ${TEST_INFERENCE_IR_PASS})
endforeach() endforeach()
...@@ -53,6 +60,14 @@ if (WITH_MKLDNN AND TENSORRT_FOUND AND WITH_GPU) ...@@ -53,6 +60,14 @@ if (WITH_MKLDNN AND TENSORRT_FOUND AND WITH_GPU)
endforeach() endforeach()
endif() endif()
if (NOT WITH_MKLDNN AND NOT TENSORRT_FOUND AND NOT WITH_GPU)
foreach(target ${TEST_INFERENCE_CPU_UT})
py_test_modules(${target} MODULES ${target})
endforeach()
set_tests_properties(test_mul_lstm_fuse_pass PROPERTIES TIMEOUT 300)
endif()
if(WITH_GPU AND TENSORRT_FOUND) if(WITH_GPU AND TENSORRT_FOUND)
set_tests_properties(test_trt_subgraph_pass PROPERTIES TIMEOUT 120) set_tests_properties(test_trt_subgraph_pass PROPERTIES TIMEOUT 120)
set_tests_properties(test_trt_activation_pass PROPERTIES TIMEOUT 120) set_tests_properties(test_trt_activation_pass PROPERTIES TIMEOUT 120)
......
# Copyright (c) 2021 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 auto_scan_test import PassAutoScanTest, SkipReasons
from program_config import TensorConfig, ProgramConfig, OpConfig
import numpy as np
import paddle.inference as paddle_infer
from functools import partial
from typing import Optional, List, Callable, Dict, Any, Set
import unittest
import hypothesis
from hypothesis import given, settings, seed, example, assume
import hypothesis.strategies as st
from functools import reduce
class TestMulLstmFusePass(PassAutoScanTest):
def is_program_valid(self, program_config: ProgramConfig) -> bool:
return True
def sample_program_config(self, draw):
x_col = draw(st.sampled_from([1]))
y_col = draw(st.sampled_from([1]))
use_peepholes = draw(st.booleans())
is_reverse = draw(st.booleans())
gate_activation = draw(st.sampled_from(["sigmoid"]))
cell_activation = draw(st.sampled_from(["tanh", "relu", "identity"]))
candidate_activation = draw(
st.sampled_from(["tanh", "relu", "identity"]))
batch_size = draw(st.integers(min_value=1, max_value=40))
def generate_input():
shape = [batch_size, 128, 6, 120]
return np.full(shape, 0.01).astype(np.float32)
def generate_weight(shape):
return np.full(shape, 0.0001).astype(np.float32)
im2sequence_op = OpConfig(
type="im2sequence",
inputs={"X": ["input_data"]},
outputs={"Out": ["seq_out"]},
attrs={
"kernels": [6, 1],
"out_stride": [1, 1],
"paddings": [0, 0, 0, 0],
"strides": [1, 1]
})
mul_op = OpConfig(
type="mul",
inputs={"X": ["seq_out"],
"Y": ["mul_weight"]},
outputs={"Out": ["mul_out"]},
attrs={"x_num_col_dims": x_col,
"y_num_col_dims": y_col})
lstm_op = OpConfig(
type="lstm",
inputs={
"Input": ["mul_out"],
"Weight": ["lstm_weight"],
"Bias": ["lstm_bias"]
},
outputs={
"Hidden": ["lstm_hidden"],
"Cell": ["lstm_cell"],
"BatchGate": ["lstm_gate"],
"BatchCellPreAct": ["lstm_batch_cell"]
},
attrs={
'use_peepholes': use_peepholes,
'is_reverse': is_reverse,
'gate_activation': gate_activation,
'cell_activation': cell_activation,
'candidate_activation': candidate_activation,
'is_test': True
})
model_net = [im2sequence_op, mul_op, lstm_op]
if use_peepholes:
lstm_bias_shape = [1, 1050]
else:
lstm_bias_shape = [1, 600]
program_config = ProgramConfig(
ops=model_net,
weights={
"mul_weight":
TensorConfig(data_gen=partial(generate_weight, [768, 600])),
"lstm_weight":
TensorConfig(data_gen=partial(generate_weight, [150, 600])),
"lstm_bias":
TensorConfig(data_gen=partial(generate_weight, lstm_bias_shape))
},
inputs={
"input_data": TensorConfig(data_gen=partial(generate_input)),
},
outputs=["lstm_hidden"])
return program_config
def sample_predictor_configs(self, program_config):
config = self.create_inference_config()
yield config, ["im2sequence", "fusion_lstm"], (1e-5, 1e-5)
def test(self):
self.run_and_statis(
quant=False, max_duration=300, passes=["mul_lstm_fuse_pass"])
if __name__ == "__main__":
unittest.main()
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