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[Cherry-Pick]Cherry pick PR41200, PR41474, PR41382 (#41509)
* Use `self`as a parameter of _hash_with_id function to avoid error caused by hash_id reuse (#41200) * Add fill_constant_batch_size YAML and UT (#41474) * Switch some dy2st UT to eager mode (#41382) * Sitch some dy2st UT to eager mode * Fix test_lstm and remove test_transformer * Run test_resnet_v2 in old dy mode
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75
python/paddle/fluid/tests/unittests/test_fill_constant_batch_size_like.py
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# Copyright (c) 2019 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. | ||
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from __future__ import print_function | ||
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import paddle | ||
import paddle.fluid.core as core | ||
from paddle.static import program_guard, Program | ||
import paddle.compat as cpt | ||
import unittest | ||
import numpy as np | ||
from op_test import OpTest | ||
from paddle.fluid.framework import convert_np_dtype_to_dtype_ | ||
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paddle.enable_static() | ||
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def fill_constant_batch_size_like(input, | ||
shape, | ||
value, | ||
data_type, | ||
input_dim_idx=0, | ||
output_dim_idx=0, | ||
force_cpu=False): | ||
return paddle.fluid.layers.fill_constant_batch_size_like( | ||
input, shape, data_type, value, input_dim_idx, output_dim_idx, | ||
force_cpu) | ||
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class TestFillConstatnBatchSizeLike1(OpTest): | ||
# test basic | ||
def setUp(self): | ||
self.op_type = "fill_constant_batch_size_like" | ||
self.python_api = fill_constant_batch_size_like | ||
self.init_data() | ||
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input = np.zeros(self.shape) | ||
out = np.full_like(input, self.value, self.dtype) | ||
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self.inputs = {'Input': input} | ||
self.outputs = {'Out': out} | ||
self.attrs = { | ||
'shape': self.shape, | ||
'dtype': convert_np_dtype_to_dtype_(self.dtype), | ||
'value': self.value, | ||
'input_dim_idx': self.input_dim_idx, | ||
'output_dim_idx': self.output_dim_idx, | ||
'force_cpu': self.force_cpu | ||
} | ||
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def init_data(self): | ||
self.shape = [10, 10] | ||
self.dtype = np.float32 | ||
self.value = 100 | ||
self.input_dim_idx = 0 | ||
self.output_dim_idx = 0 | ||
self.force_cpu = False | ||
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def test_check_output(self): | ||
self.check_output(check_eager=True) | ||
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if __name__ == "__main__": | ||
unittest.main() |
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