- Sort Score
- Result 10 results
- Languages All
Results 11 - 20 of 45 for x1_shape (0.21 sec)
-
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/gradients/manip_grad_test.cc
ManipGradTest() : scope_(Scope::NewRootScope()) {} void RunTest(const Output& x, const TensorShape& x_shape, const Output& y, const TensorShape& y_shape) { TF_ASSERT_OK(scope_.status()); float max_error; TF_ASSERT_OK((ComputeGradientError<float, float, float>( scope_, {x}, {x_shape}, {y}, {y_shape}, &max_error))); EXPECT_LT(max_error, 1e-4); } Scope scope_; };
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Mar 19 12:19:42 UTC 2020 - 1.6K 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/compiler/mlir/quantization/tensorflow/python/integration_test/quantize_model_test_base.py
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: Thu Mar 21 08:51:46 UTC 2024 - 51.2K bytes - Viewed (0) -
tensorflow/cc/framework/gradient_checker.h
template <typename X_T, typename Y_T, typename JAC_T> Status ComputeGradientError(const Scope& scope, const OutputList& xs, const std::vector<TensorShape>& x_shapes, const OutputList& ys, const std::vector<TensorShape>& y_shapes, JAC_T* max_error);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Oct 05 15:35:17 UTC 2022 - 2.8K 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/cc/gradients/image_grad.cc
// The internal gradient implementation needs the shape of the input image. // x_shape = shape(x)[1:3] // = slice(shape(x), {1}, {3 - 1}) auto x_shape = Slice(scope, Shape(scope, op.input(0)), {1}, {2}); grad_outputs->push_back(internal::ResizeNearestNeighborGrad( scope, grad_inputs[0], x_shape, internal::ResizeNearestNeighborGrad::AlignCorners(align_corners)
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Nov 11 00:29:23 UTC 2021 - 5.7K bytes - Viewed (0)