/external/tensorflow/tensorflow/python/ops/ |
D | nn_fused_batchnorm_test.py | 66 exponential_avg_factor=1.0, argument 89 exponential_avg_factor=exponential_avg_factor, 108 exponential_avg_factor, epsilon, data_format): argument 136 mean = self._running_mean(old_mean, batch_mean, exponential_avg_factor) 138 exponential_avg_factor) 147 exponential_avg_factor=1.0, argument 153 if exponential_avg_factor == 1.0: 172 exponential_avg_factor=exponential_avg_factor, 178 exponential_avg_factor, 228 exponential_avg_factor=1.0, argument [all …]
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D | nn_impl.py | 1594 exponential_avg_factor=1.0): argument 1657 if (not is_training or exponential_avg_factor != 1.0) and ( 1682 exponential_avg_factor=exponential_avg_factor,
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/external/tensorflow/tensorflow/compiler/tests/ |
D | fused_batchnorm_test.py | 48 exponential_avg_factor, data_format): argument 60 if exponential_avg_factor != 1.0: 62 exponential_avg_factor) * old_mean + exponential_avg_factor * mean 63 corrected_var = (1.0 - exponential_avg_factor 64 ) * old_var + exponential_avg_factor * corrected_var 97 exponential_avg_factor = 1.0 101 exponential_avg_factor, data_format_src) 133 exponential_avg_factor): argument 148 exponential_avg_factor, data_format_src) 162 if exponential_avg_factor == 1.0: [all …]
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/external/tensorflow/tensorflow/core/kernels/mkl/ |
D | mkl_fused_batch_norm_op_test.cc | 47 const float exponential_avg_factor, const bool is_training, Tensor* output, 79 static void VerifyTensorsClose(const float exponential_avg_factor, in VerifyTensorsClose() argument 95 if (is_training && (exponential_avg_factor == 1.0)) { in VerifyTensorsClose() 111 run(input, scale, offset, mean, variance, exponential_avg_factor, in VerifyTensorsClose() 113 run_mkl(input, scale, offset, mean, variance, exponential_avg_factor, in VerifyTensorsClose() 224 void VerifyFusedBatchNorm(const float exponential_avg_factor, in VerifyFusedBatchNorm() argument 229 const float exponential_avg_factor, in VerifyFusedBatchNorm() 246 attr = attr.ExponentialAvgFactor(exponential_avg_factor); in VerifyFusedBatchNorm() 275 const float exponential_avg_factor, in VerifyFusedBatchNorm() 291 .Attr("exponential_avg_factor", exponential_avg_factor) in VerifyFusedBatchNorm() [all …]
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D | mkl_fused_batch_norm_op.cc | 646 float exponential_avg_factor; in MklFusedBatchNormOp() local 648 &exponential_avg_factor)); in MklFusedBatchNormOp() 649 exponential_avg_factor_ = static_cast<U>(exponential_avg_factor); in MklFusedBatchNormOp()
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/external/tensorflow/tensorflow/compiler/mlir/tensorflow/tests/ |
D | layout_optimization_layout_assignment_gpu_cc_60.mlir | 79 exponential_avg_factor = 1.0 : f32, 104 exponential_avg_factor = 1.0 : f32, 130 exponential_avg_factor = 1.0 : f32, 156 exponential_avg_factor = 1.0 : f32,
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D | layout_optimization_layout_assignment_gpu_cc_70.mlir | 160 exponential_avg_factor = 1.0 : f32, 185 exponential_avg_factor = 1.0 : f32, 211 exponential_avg_factor = 1.0 : f32, 237 exponential_avg_factor = 1.0 : f32,
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D | layout_optimization_layout_assignment_to_nchw.mlir | 176 exponential_avg_factor = 1.0 : f32, 218 exponential_avg_factor = 1.0 : f32,
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D | layout_optimization_layout_assignment_to_nhwc.mlir | 63 exponential_avg_factor = 1.0 : f32,
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D | layout_optimization_move_transposes_end.mlir | 121 exponential_avg_factor = 1.0 : f32,
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/external/tensorflow/tensorflow/core/ops/compat/ops_history_v2/ |
D | FusedBatchNormV3.pbtxt | 75 name: "exponential_avg_factor" 176 name: "exponential_avg_factor"
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D | FusedBatchNorm.pbtxt | 139 name: "exponential_avg_factor"
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D | FusedBatchNormV2.pbtxt | 161 name: "exponential_avg_factor"
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/external/tensorflow/tensorflow/core/kernels/ |
D | fused_batch_norm_op.cc | 97 const Tensor* side_input, U epsilon, U exponential_avg_factor, in operator ()() 201 if (exponential_avg_factor == U(1.0)) { in operator ()() 207 U one_minus_factor = U(1) - exponential_avg_factor; in operator ()() 212 (exponential_avg_factor * rest_size_adjust) * batch_variance; in operator ()() 214 one_minus_factor * old_mean + exponential_avg_factor * batch_mean; in operator ()() 235 const Tensor* side_input, U epsilon, U exponential_avg_factor, in operator ()() 763 U epsilon, U exponential_avg_factor, in operator ()() 933 exponential_avg_factor != 1.0f) { in operator ()() 944 exponential_avg_factor != 1.0f) { in operator ()() 960 static_cast<double>(exponential_avg_factor), in operator ()() [all …]
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/external/tensorflow/tensorflow/compiler/mlir/tensorflow/tests/compile_mlir_util/ |
D | shape-inference-after-legalization.mlir | 6 …ata_format = "NHWC", device = "", epsilon = 9.99999974E-5 : f32, exponential_avg_factor = 1.000000…
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/external/tensorflow/tensorflow/core/ops/compat/ops_history_v1/ |
D | FusedBatchNorm.pbtxt | 139 name: "exponential_avg_factor"
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D | FusedBatchNormV2.pbtxt | 161 name: "exponential_avg_factor"
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D | FusedBatchNormV3.pbtxt | 169 name: "exponential_avg_factor"
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/external/tensorflow/tensorflow/core/ops/ |
D | nn_ops_test.cc | 184 auto set_op = [&op](bool is_training, float exponential_avg_factor, in TEST() 194 .Attr("exponential_avg_factor", exponential_avg_factor) in TEST()
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/external/tensorflow/tensorflow/python/keras/layers/ |
D | normalization.py | 560 exponential_avg_factor = 1.0 - self.momentum 562 exponential_avg_factor = None 593 exponential_avg_factor=exponential_avg_factor)
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/external/tensorflow/tensorflow/compiler/mlir/lite/transforms/ |
D | prepare_tf.cc | 991 ::mlir::FloatAttr exponential_avg_factor; in matchAndRewrite() 1031 exponential_avg_factor = in matchAndRewrite() 1034 if (!exponential_avg_factor) in matchAndRewrite() 1035 exponential_avg_factor = in matchAndRewrite()
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/external/tensorflow/tensorflow/core/framework/ |
D | common_shape_fns.cc | 1146 float exponential_avg_factor; in FusedBatchNormShape() local 1147 if (!c->GetAttr("exponential_avg_factor", &exponential_avg_factor).ok()) { in FusedBatchNormShape() 1148 exponential_avg_factor = 1.0f; // default value in FusedBatchNormShape() 1150 int number_inputs = (is_training && exponential_avg_factor == 1.0f) ? 3 : 5; in FusedBatchNormShape()
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/external/tensorflow/tensorflow/compiler/mlir/lite/tests/ |
D | prepare-tf.mlir | 724 …arg4) {data_format = "NHWC", device = "", epsilon = 0.001 : f32, exponential_avg_factor = 1.0 : f3… 745 …data_format = "NHWC", device = "", epsilon = 1.000000e-03 : f32, exponential_avg_factor = 1.000000… 766 …data_format = "NHWC", device = "", epsilon = 1.000000e-03 : f32, exponential_avg_factor = 1.000000… 788 …rg3, %arg4) {data_format = "NHWC", epsilon = 1.000000e-03 : f32, exponential_avg_factor = 1.000000…
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/external/tensorflow/tensorflow/tools/api/golden/v1/ |
D | tensorflow.nn.pbtxt | 213 …ce\', \'epsilon\', \'data_format\', \'is_training\', \'name\', \'exponential_avg_factor\'], vararg…
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/external/tensorflow/tensorflow/compiler/mlir/xla/transforms/ |
D | legalize_tf_patterns.td | 61 $exponential_avg_factor, $data_format,
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