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Results 1 - 10 of 15 for x1_shape (0.26 sec)
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tensorflow/cc/gradients/math_grad_test.cc
auto y = Sub(scope_, x1, x2); RunTest({x1, x2}, {x1_shape, x2_shape}, {y}, {x1_shape}); } TEST_F(NaryGradTest, Mul) { TensorShape x1_shape({3, 2, 5}); TensorShape x2_shape({2, 5}); auto x1 = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x1_shape)); auto x2 = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x2_shape)); auto y = Mul(scope_, x1, x2);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Aug 25 18:20:20 UTC 2023 - 36K bytes - Viewed (0) -
tensorflow/cc/gradients/array_grad_test.cc
RunTest(x, x_shape, y, y_shape); } TEST_F(ArrayGradTest, DiagPartGrad) { TensorShape x_shape({5, 2, 5, 2}); auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape)); auto y = DiagPart(scope_, x); TensorShape y_shape({5, 2}); RunTest(x, x_shape, y, y_shape); } TEST_F(ArrayGradTest, MatrixDiagGrad) { TensorShape x_shape({5, 2});
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Oct 10 23:33:32 UTC 2023 - 19.3K bytes - Viewed (0) -
tensorflow/cc/gradients/nn_grad_test.cc
auto y = AvgPool3D(scope_, x, ksize, strides, "SAME"); RunTest(x, x_shape, y, y_shape); } TEST_F(NNGradTest, LRN) { TensorShape x_shape({1, 1, 2, 1}); auto x = Placeholder(scope_, DT_FLOAT, Placeholder::Shape(x_shape)); auto y = LRN(scope_, x); RunTest(x, x_shape, y, x_shape); } TEST_F(NNGradTest, SoftplusGrad) { TensorShape shape({3, 7});
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 22 20:45:22 UTC 2022 - 15K bytes - Viewed (0) -
tensorflow/cc/gradients/image_grad_test.cc
} template <typename T> void TestResizedShapeForType(const OpType op_type, const bool align_corners, const bool half_pixel_centers) { TensorShape x_shape({1, 2, 2, 1}); Tensor x_data = MakeData<T>(x_shape); Output x, y; MakeOp<T>(op_type, x_data, {4, 6}, align_corners, half_pixel_centers, &x, &y); ClientSession session(scope_); std::vector<Tensor> outputs;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Mar 15 04:08:05 UTC 2019 - 12.1K bytes - Viewed (0) -
tensorflow/cc/framework/gradient_checker.cc
const std::vector<TensorShape>& x_shapes, const OutputList& ys, const std::vector<TensorShape>& y_shapes, JAC_T* max_error) { if (xs.size() != x_shapes.size()) { return errors::InvalidArgument("xs(size ", xs.size(), ") and x_shapes(size ", x_shapes.size(),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 13 05:57:22 UTC 2024 - 18.2K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_tpu_device.cc
XlaLayoutPreference layout_preference) { xla::Shape xla_shape; TF_RETURN_IF_ERROR( tensorflow::TensorShapeToXLAShape(type, shape, &xla_shape)); ApiConverter::StackHelper<XLA_Shape> se_shape(xla_shape); ApiConverter::StackHelper<XLA_Shape> tpu_shape; StatusHelper status; stream_executor::tpu::ExecutorApiFn()->XlaShapeToTpuShapeRepresentationFn( &se_shape.value, type, use_fast_memory, &tpu_shape.value,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 28 22:53:47 UTC 2024 - 20.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/quantization/stablehlo/python/integration_test/quantize_model_test_base.py
contracting_dims.add(c) x_signature = [ None if c not in contracting_dims else x_shape[cidx] for cidx, c in enumerate(x_labels) ] y_signature = [ None if c not in contracting_dims else y_shape[cidx] for cidx, c in enumerate(y_labels) ] return x_shape, y_shape, bias_shape, x_signature, y_signature def _create_einsum_model( self,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 14 06:31:57 UTC 2024 - 18.2K bytes - Viewed (0) -
tensorflow/cc/gradients/linalg_grad.cc
x = Conj(scope, x); y = Conj(scope, y); } const auto x_shape = Shape(scope, x); const auto y_shape = Shape(scope, y); Output grad_x = EinsumGradWrt(scope, grad, y, x_shape, x_subs, y_subs, output_subs); Output grad_y = EinsumGradWrt(scope, grad, x, y_shape, y_subs, x_subs, output_subs); if (!absl::StrContains(output_subs, kEllipsis)) {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Mon Mar 07 23:11:54 UTC 2022 - 20.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/tests/unfuse_mhlo_batch_norm.mlir
// CHECK-DAG: %[[RHS:.+]] = mhlo.subtract %[[OFFSET]], %[[MUL_MEAN]] : tensor<?xf32> // CHECK-DAG: %[[X_SHAPE:.+]] = shape.shape_of %[[X]] : tensor<?x?x?x?xf32> -> tensor<4xindex> // CHECK-DAG: %[[MULTIPLIER_BCAST:.+]] = "mhlo.dynamic_broadcast_in_dim"(%[[MULTIPLIER]], %[[X_SHAPE]]) <{broadcast_dimensions = dense<1> : tensor<1xi64>}> : (tensor<?xf32>, tensor<4xindex>) -> tensor<?x?x?x?xf32>
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 06 15:32:52 UTC 2024 - 10.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/utils/utils.h
std::vector<int64_t> in_shape{input_type.getShape().vec()}; std::vector<int64_t> out_shape{output_type.getShape().vec()}; // If the reshape changes the number of dimensions so it cannot be interpreted // as a transpose. if (in_shape.size() != out_shape.size()) { return false; } in_shape.erase(std::remove(in_shape.begin(), in_shape.end(), 1), in_shape.end());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 30 00:40:15 UTC 2024 - 11.6K bytes - Viewed (0)