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Results 11 - 16 of 16 for xla_tensor (0.12 sec)
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tensorflow/compiler/jit/xla_device.h
#ifndef TENSORFLOW_COMPILER_JIT_XLA_DEVICE_H_ #define TENSORFLOW_COMPILER_JIT_XLA_DEVICE_H_ #include <set> #include "absl/types/optional.h" #include "tensorflow/compiler/jit/xla_tensor.h" #include "tensorflow/compiler/tf2xla/layout_util.h" #include "tensorflow/compiler/tf2xla/xla_compiler.h" #include "tensorflow/compiler/tf2xla/xla_op_registry.h" #include "xla/client/local_client.h"
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Wed Feb 21 09:53:30 UTC 2024 - 13.4K bytes - Viewed (0) -
tensorflow/c/eager/dlpack.cc
DLManagedTensor* dlm_tensor = &tf_dlm_tensor_ctx->tensor; dlm_tensor->manager_ctx = tf_dlm_tensor_ctx; dlm_tensor->deleter = &DLManagedTensorDeleter; dlm_tensor->dl_tensor.device = tf_dlm_context; int ndim = tensor->dims(); dlm_tensor->dl_tensor.ndim = ndim; dlm_tensor->dl_tensor.data = tf_dlm_data; dlm_tensor->dl_tensor.dtype = tf_dlm_type;
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 15 09:49:45 UTC 2024 - 12.8K bytes - Viewed (0) -
tensorflow/c/eager/dlpack_test.cc
num_elements *= shape[i]; } std::vector<float> data(num_elements); for (size_t j = 0; j < num_elements; ++j) { data[j] = j; } DLManagedTensor dlm_in = {}; DLTensor* dltensor_in = &dlm_in.dl_tensor; dltensor_in->data = data.data(); dltensor_in->device = {kDLCPU, 0}; dltensor_in->ndim = static_cast<int32_t>(shape.size()); dltensor_in->dtype = {kDLFloat, 32, 1}; dltensor_in->shape = shape.data();
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Fri Jun 30 03:04:46 UTC 2023 - 4.4K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/remat/rematerializer.cc
for (const int old_tensor : std::vector<int>(operations_[iop].tensors)) { const auto new_tensor = std::lower_bound(new_tensors.begin(), new_tensors.end(), std::make_pair(old_tensor, 0)); if (new_tensor != new_tensors.end() && new_tensor->first == old_tensor) { DelUse(iop, old_tensor); AddUse(iop, new_tensor->second); } }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 14 20:57:44 UTC 2023 - 13.7K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_cpu_device.cc
// context in tensorflow_accelerator_device_info(). Also, // tensorflow_accelerator_device_info() == nullptr is used as an IsCPU test. // We need XlaCpuDevice to be treated not as CPU because it allocates // XlaTensors, not regular Tensors. Status status = device->UseAcceleratorDeviceInfo(); if (!status.ok()) { errors::AppendToMessage(&status, "while setting up ", DEVICE_GPU_XLA_JIT); return status; }
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu Feb 22 08:47:20 UTC 2024 - 5.5K bytes - Viewed (0) -
tensorflow/compiler/jit/xla_platform_info.cc
// // Importantly we can't use ctx->device()->GetAllocator() as the allocator // (which xla_allocator above uses) as on an XlaDevice, this is a dummy // allocator that returns XlaTensor objects. The XlaCompiler needs a real // allocator to allocate real buffers. platform_id = xla_device_metadata->platform()->id(); custom_allocator =
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Thu May 02 17:23:27 UTC 2024 - 17.4K bytes - Viewed (0)