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python/paddle/fluid/tests/unittests/mkldnn/test_fusion_gru_bf16_mkldnn_op.py
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| # Copyright (c) 2018 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 unittest | ||
| import numpy as np | ||
| import struct | ||
| from paddle.fluid.tests.unittests.op_test import OpTest, convert_float_to_uint16 | ||
| from paddle.fluid.tests.unittests.op_test import OpTest | ||
| from paddle.fluid.tests.unittests.test_fusion_gru_op import fusion_gru | ||
| from paddle.fluid.tests.unittests.test_fusion_lstm_op import fc, ACTIVATION | ||
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| @unittest.skipIf(not core.supports_bfloat16(), | ||
| "place does not support BF16 evaluation") | ||
| class TestFusionGRUBF16MKLDNNOp(OpTest): | ||
| def set_confs(self): | ||
| self.mkldnn_data_type = False | ||
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| def setUp(self): | ||
| self.op_type = "fusion_gru" | ||
| self.lod = [[2, 4, 3]] | ||
| self.M = 3 | ||
| self.D = 5 | ||
| self.is_reverse = False | ||
| self.with_h0 = False | ||
| self.use_mkldnn = True | ||
| self._cpu_only = True | ||
| self.with_bias = True | ||
| self.act_state = 'tanh' | ||
| self.act_gate = 'sigmoid' | ||
| self.origin_mode = False | ||
| self.use_mkldnn = True | ||
| self.force_fp32_output = False | ||
| self.set_confs() | ||
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| T = sum(self.lod[0]) | ||
| N = len(self.lod[0]) | ||
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| # fp32 X input for reference implementation and | ||
| # corressponding bf16 data as input to GRU oneDNN bf16 kernel | ||
| x_fp32 = np.random.rand(T, self.M).astype('float32') | ||
| x_bf16 = convert_float_to_uint16(x_fp32) | ||
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| wx_fp32 = np.random.rand(self.M, 3 * self.D).astype('float32') | ||
| wh_fp32 = np.random.rand(self.D, 3 * self.D).astype('float32') | ||
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| # bias is fp32 despite other inputs being in bf16 | ||
| bias = np.random.rand( | ||
| 1, 3 * self.D).astype('float32') if self.with_bias else np.zeros( | ||
| (1, 3 * self.D), dtype='float32') | ||
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| h0_fp32 = np.random.rand( | ||
| N, self.D).astype('float32') if self.with_h0 else np.zeros( | ||
| (N, self.D), dtype='float32') | ||
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| _, _, _, hidden = fusion_gru( | ||
| x_fp32, self.lod, h0_fp32, wx_fp32, wh_fp32, bias, self.is_reverse, | ||
| self.origin_mode, ACTIVATION[self.act_state], | ||
| ACTIVATION[self.act_gate]) | ||
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| hidden_bf16 = convert_float_to_uint16(hidden) | ||
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| self.inputs = { | ||
| 'X': (x_bf16, self.lod), | ||
| 'WeightX': wx_fp32, | ||
| 'WeightH': wh_fp32 | ||
| } | ||
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| if self.with_bias: | ||
| self.inputs['Bias'] = bias | ||
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| if self.with_h0: | ||
| self.inputs['H0'] = h0_bf16 | ||
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| h0_bf16 = convert_float_to_uint16(h0_fp32) | ||
| self.outputs = {'Hidden': (hidden_bf16, self.lod)} | ||
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| self.attrs = { | ||
| 'activation': self.act_state, | ||
| 'gate_activation': self.act_gate, | ||
| 'is_reverse': self.is_reverse, | ||
| 'origin_mode': self.origin_mode, | ||
| 'force_fp32_output': self.force_fp32_output, | ||
| 'use_mkldnn': self.use_mkldnn | ||
| } | ||
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| class TestFusionGRUINT8MKLDNNOp2(TestFusionGRUBF16MKLDNNOp): | ||
| def set_confs(self): | ||
| self.origin_mode = False | ||
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| class TestFusionGRUINT8MKLDNNOp3(TestFusionGRUBF16MKLDNNOp): | ||
| def set_confs(self): | ||
| self.with_bias = False | ||
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| if __name__ == "__main__": | ||
| unittest.main() |