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tensorflow/cc/experimental/base/tests/tensorhandle_test.cc
ASSERT_TRUE(status.ok()) << status.message(); TF_DataType dtype = TypeParam::kDType; // This is our 1D tensor of varying dtype. std::vector<typename TypeParam::type> value = {42, 100, 0, 1, 4, 29}; // Shape is Rank 2 vector with shape 2 x 3. std::vector<int64_t> shape({2, 3}); Tensor original_tensor = Tensor::FromBuffer( /*dtype=*/dtype, /*shape=*/shape, /*data=*/value.data(),
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 13 09:56:08 UTC 2024 - 6.9K bytes - Viewed (0) -
tensorflow/compiler/mlir/tensorflow/utils/convert_type.cc
switch (itype.getWidth()) { case 1: *dtype = DT_BOOL; return absl::OkStatus(); case 4: *dtype = itype.isUnsigned() ? DT_UINT4 : DT_INT4; return absl::OkStatus(); case 8: *dtype = itype.isUnsigned() ? DT_UINT8 : DT_INT8; return absl::OkStatus(); case 16:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Apr 26 09:37:10 UTC 2024 - 7.5K bytes - Viewed (0) -
tensorflow/c/tf_tensor.cc
return CreateTensor(buf, dtype, dims, num_dims, len); } TF_Tensor* TF_NewTensor(TF_DataType dtype, const int64_t* dims, int num_dims, void* data, size_t len, void (*deallocator)(void* data, size_t len, void* arg), void* deallocator_arg) { TF_ManagedBuffer* buf = nullptr; if (dtype != TF_STRING && dtype != TF_RESOURCE &&
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sun Apr 14 21:57:32 UTC 2024 - 11.5K bytes - Viewed (0) -
tensorflow/cc/experimental/libtf/impl/tensor_spec_test.cc
tensorflow::PartialTensorShape unknown_shape; TensorSpec ts1; ts1.shape = unknown_shape; ts1.dtype = tensorflow::DT_FLOAT; TensorSpec ts2; ts2.shape = tensorflow::PartialTensorShape({2}); ts2.dtype = tensorflow::DT_FLOAT; TensorSpec ts3; ts3.shape = tensorflow::PartialTensorShape({1, 2}); ts3.dtype = tensorflow::DT_FLOAT; EXPECT_TRUE(absl::VerifyTypeImplementsAbslHashCorrectly({ts1, ts2, ts3})); }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 18 09:47:46 UTC 2024 - 1.5K bytes - Viewed (0) -
tensorflow/cc/experimental/base/tests/tensor_test.cc
Tensor tensor = Tensor::FromBuffer( /*dtype=*/dtype, /*shape=*/shape, /*data=*/value.data(), /*len=*/value.size() * sizeof(typename TypeParam::type), /*deleter=*/[](void*, size_t) {}, &status); ASSERT_TRUE(status.ok()) << status.message(); EXPECT_EQ(tensor.dims(), 1); EXPECT_EQ(tensor.dtype(), dtype); absl::Span<const typename TypeParam::type> tensor_view(
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Sat Apr 13 09:56:08 UTC 2024 - 6K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/stablehlo/transforms/op_stat_pass.cc
auto operand_or_result = value_shaped_type.getElementType(); std::string dtype; TypeSwitch<Type>(operand_or_result) .Case<IntegerType>([&](Type) { dtype = absl::StrCat("i", operand_or_result.getIntOrFloatBitWidth()); }) .Case<FloatType>([&](Type) { dtype = absl::StrCat("f", operand_or_result.getIntOrFloatBitWidth());
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Apr 25 16:01:03 UTC 2024 - 8.7K bytes - Viewed (0) -
tensorflow/c/experimental/saved_model/core/ops/variable_ops.cc
DataType dtype, TensorShape shape, const char* raw_device_name, ImmediateTensorHandlePtr* handle) { ImmediateOpPtr varhandle_op(ctx->CreateOperation()); TF_RETURN_IF_ERROR(varhandle_op->Reset("VarHandleOp", raw_device_name)); TF_RETURN_IF_ERROR(varhandle_op->SetAttrType("dtype", dtype));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Apr 23 11:28:19 UTC 2024 - 5K bytes - Viewed (0) -
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/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)