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tensorflow/cc/experimental/libtf/impl/iostream_test.cc
} TEST(OStreamTest, TestTensorSpec) { std::stringstream stream; TensorSpec tensor_spec; tensor_spec.shape = tensorflow::PartialTensorShape({2}); tensor_spec.dtype = tensorflow::DT_FLOAT; stream << tensor_spec; ASSERT_EQ(stream.str(), "TensorSpec(shape = [2], dtype = 1)"); } } // namespace impl } // namespace libtf
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 09:47:46 UTC 2024 - 2K bytes - Viewed (0) -
tensorflow/compiler/jit/shape_inference.cc
DataType dtype = n->output_type(0); AddNodeAttr("dtype", dtype, &const_def); TensorProto value; value.set_dtype(dtype); value.mutable_tensor_shape()->add_dim()->set_size( shape_proto.dim_size()); for (const auto& dim : shape_proto.dim()) { if (dtype == DT_INT32) { value.add_int_val(dim.size());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 31 00:41:19 UTC 2024 - 13K bytes - Viewed (0) -
tensorflow/compiler/mlir/tfrt/saved_model/saved_model.cc
absl::StatusOr<std::pair<tensorflow::DataType, tensorflow::PartialTensorShape>> ProcessTensorSpec(mlir::TensorType type) { tensorflow::DataType dtype; TF_RETURN_IF_ERROR( ConvertScalarTypeToDataType(type.getElementType(), &dtype)); if (!type.hasRank()) return std::make_pair(dtype, tensorflow::PartialTensorShape()); auto shape = type.getShape(); llvm::SmallVector<int64_t, 4> dims; dims.assign(shape.begin(), shape.end());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 5.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/tests/end2end/unroll_batch_matmul.pbtxt
node { name: "Placeholder" op: "Placeholder" attr { key: "dtype" value { type: DT_FLOAT } } attr { key: "shape" value { shape { dim { size: 2 } dim { size: 5 } dim {
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 09:41:17 UTC 2024 - 2.6K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_host_recv_device_context.cc
Tensor* cpu_tensor, StatusCallback done) { DataType dtype = EncodePrimitiveTypeAsDataType(shape_.element_type()).value(); TensorShape tensor_shape; Status status = XLAShapeToTensorShape(shape_, &tensor_shape); if (!status.ok()) { done(status); return; } *cpu_tensor = Tensor(dtype, tensor_shape); status = stream_->Memcpy(cpu_tensor->data(), device_memory_base_,
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri May 17 22:46:36 UTC 2024 - 1.9K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_launch_util.cc
// Copy XLA results to the OpOutputList. int output_num = 0; for (int i = 0, end = ctx->num_outputs(); i < end; ++i) { const DataType& type = compilation_result.outputs[i].type; VLOG(2) << "Populating output for retval " << i << " type " << DataTypeString(type); if (type == DT_VARIANT) { return absl::UnimplementedError( "Support for TensorList crossing the XLA/TF boundary "
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 16 00:36:08 UTC 2024 - 40.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow_to_stablehlo/python/integration_test/tensorflow_to_stablehlo_test.py
class AddOneModel(tf.keras.Model): def call(self, x): return x + 1 model = AddOneModel() x_train = tf.constant([1, 2, 3, 4, 5], dtype=tf.float32) y_train = tf.constant([2, 3, 4, 5, 6], dtype=tf.float32) model.compile(optimizer='sgd', loss='mse') model.fit(x_train, y_train, epochs=1) path = tempdir + '/add_one_model' model.save(path) return path
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue May 21 22:58:42 UTC 2024 - 2.7K bytes - Viewed (0) -
src/cmd/cgo/gcc.go
func (p *Package) recordTypedefs(dtype dwarf.Type, pos token.Pos) { p.recordTypedefs1(dtype, pos, map[dwarf.Type]bool{}) } func (p *Package) recordTypedefs1(dtype dwarf.Type, pos token.Pos, visited map[dwarf.Type]bool) { if dtype == nil { return } if visited[dtype] { return } visited[dtype] = true switch dt := dtype.(type) { case *dwarf.TypedefType:
Registered: Wed Jun 12 16:32:35 UTC 2024 - Last Modified: Mon May 20 15:50:06 UTC 2024 - 97K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/convert_tensor_test.cc
class ConvertTensorTest : public ::testing::Test { protected: template <typename T> void VerifyConversion(std::initializer_list<T> values, DataType dtype, mlir::Type expected_ty) { mlir::Builder b(expected_ty.getContext()); Tensor tensor(dtype, TensorShape({static_cast<int64_t>(values.size())})); tensor.flat<T>().setValues(values); auto value_or = ConvertTensor(tensor, &b);
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 10.4K bytes - Viewed (0) -
tensorflow/compiler/jit/pjrt_device_context.cc
shape_determination_fns.layout_preference_fn( cpu_tensor->shape(), cpu_tensor->dtype(), std::nullopt); TF_ASSIGN_OR_RETURN(xla::Shape shape, shape_determination_fns.shape_representation_fn( cpu_tensor->shape(), cpu_tensor->dtype(), /*fast_mem=*/false, layout_preference)); const xla::Layout* device_layout = &(shape.layout());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 13 08:49:31 UTC 2024 - 11.6K bytes - Viewed (0)