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Searched refs:temp_outputs (Results 1 – 5 of 5) sorted by relevance

/external/tensorflow/tensorflow/c/eager/
Dmnist_gradients_testutil.cc120 vector<AbstractTensorHandle*> temp_outputs(1); in MNISTForwardModel() local
122 TF_RETURN_IF_ERROR(ops::MatMul(ctx, {X, W1}, absl::MakeSpan(temp_outputs), in MNISTForwardModel()
127 TF_RETURN_IF_ERROR(ops::Relu(ctx, {temp_outputs[0]}, in MNISTForwardModel()
128 absl::MakeSpan(temp_outputs), in MNISTForwardModel()
132 ctx, {temp_outputs[0], W2}, absl::MakeSpan(temp_outputs), "matmul1", in MNISTForwardModel()
135 AbstractTensorHandle* scores = temp_outputs[0]; in MNISTForwardModel()
137 temp_outputs.resize(2); in MNISTForwardModel()
139 ctx, {scores, y_labels}, absl::MakeSpan(temp_outputs), in MNISTForwardModel()
142 AbstractTensorHandle* loss_vals = temp_outputs[0]; in MNISTForwardModel()
175 vector<AbstractTensorHandle*> temp_outputs(1); in MNISTGradModel() local
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Dgradients_util.cc185 vector<AbstractTensorHandle*> temp_outputs(1); in UpdateWeights() local
190 absl::MakeSpan(temp_outputs), in UpdateWeights()
192 learning_rate = temp_outputs[0]; in UpdateWeights()
198 absl::MakeSpan(temp_outputs), in UpdateWeights()
201 AbstractTensorHandle* dW = temp_outputs[0]; in UpdateWeights()
206 absl::MakeSpan(temp_outputs), in UpdateWeights()
210 weights[i] = temp_outputs[0]; in UpdateWeights()
/external/tensorflow/tensorflow/c/experimental/gradients/
Dnn_grad_test.cc46 std::vector<AbstractTensorHandle*> temp_outputs(1); in ReluGradModel() local
49 absl::MakeSpan(temp_outputs), "ReluGrad")); in ReluGradModel()
51 TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx, /*targets=*/temp_outputs, in ReluGradModel()
54 for (auto temp_output : temp_outputs) { in ReluGradModel()
63 std::vector<AbstractTensorHandle*> temp_outputs(2); in SparseSoftmaxCrossEntropyWithLogitsModel() local
65 ctx, inputs, absl::MakeSpan(temp_outputs), in SparseSoftmaxCrossEntropyWithLogitsModel()
71 outputs[0] = temp_outputs[0]; in SparseSoftmaxCrossEntropyWithLogitsModel()
72 temp_outputs[1]->Unref(); in SparseSoftmaxCrossEntropyWithLogitsModel()
87 std::vector<AbstractTensorHandle*> temp_outputs(2); in SparseSoftmaxCrossEntropyWithLogitsGradModel() local
90 tape_ctx.get(), inputs, absl::MakeSpan(temp_outputs), in SparseSoftmaxCrossEntropyWithLogitsGradModel()
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Dmath_grad.cc340 vector<AbstractTensorHandle*> temp_outputs(1); in Compute() local
345 Conj(ctx, {X}, absl::MakeSpan(temp_outputs), name.c_str())); in Compute()
347 AbstractTensorHandlePtr Conj_X(temp_outputs[0]); in Compute()
352 absl::MakeSpan(temp_outputs), name.c_str())); in Compute()
354 AbstractTensorHandlePtr Ones_X(temp_outputs[0]); in Compute()
359 absl::MakeSpan(temp_outputs), name.c_str())); in Compute()
361 AbstractTensorHandlePtr Conj_XP1(temp_outputs[0]); in Compute()
420 vector<AbstractTensorHandle*> temp_outputs(1); in Compute() local
423 TF_RETURN_IF_ERROR(Neg(ctx, {upstream_grad}, absl::MakeSpan(temp_outputs), in Compute()
425 AbstractTensorHandlePtr MinusU(temp_outputs[0]); in Compute()
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Dgrad_test_helper.cc119 std::vector<AbstractTensorHandle*> temp_outputs(1); in BuildGradModel() local
122 forward_model(tape_ctx.get(), inputs, absl::MakeSpan(temp_outputs))); in BuildGradModel()
124 TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx, /*targets=*/temp_outputs, in BuildGradModel()
127 for (auto temp_output : temp_outputs) { in BuildGradModel()