buf = new TF_ManagedBuffer(tensorflow::allocate_tensor("TF_NewTensor", len),
                               len, tensorflow::deallocate_buffer, nullptr,
                               /*owns_memory=*/true);
    std::memcpy(buf->data(), data, len);
    // Free the original buffer.
    deallocator(data, len, deallocator_arg);
  } else {
    buf = new TF_ManagedBuffer(data, len, deallocator, deallocator_arg,

  absl::Status s = cc_ctx->GetAttr(attr_name, &v);
  ::tensorflow::Set_TF_Status_from_Status(status, s);

  if (!status->status.ok()) return;

  if (max_length <= 0) {
    return;
  }
  std::memcpy(value, v.data(), std::min<size_t>(v.length(), max_length));
}

void TF_OpKernelConstruction_GetAttrStringList(TF_OpKernelConstruction* ctx,
                                               const char* attr_name,

      // Check if `dst` is in a different cluster, unclustered, or about to be
      // partially declustered (here we rely on the post-order traversal order).
      // If yes, decluster `n` to avoid the device-to-host memcpy.
      std::optional<absl::string_view> dst_cluster =
          result->count(dst) ? std::nullopt : GetXlaClusterForNode(*dst);
      if (from_cluster != dst_cluster) {
        CHECK(result->insert(n).second);

		X))
}

// issue 30065

func test30065(t *testing.T) {
	var a [256]byte
	b := []byte("a")
	C.memcpy(unsafe.Pointer(&a), unsafe.Pointer(&b[0]), 1)
	if a[0] != 'a' {
		t.Errorf("&a failed: got %c, want %c", a[0], 'a')
	}

	b = []byte("b")
	C.memcpy(unsafe.Pointer(&a[0]), unsafe.Pointer(&b[0]), 1)
	if a[0] != 'b' {
		t.Errorf("&a[0] failed: got %c, want %c", a[0], 'b')
	}

  status->status = s->session->PRunSetup(input_names, output_names,
                                         target_oper_names, &new_handle);
  if (status->status.ok()) {
    char* buf = new char[new_handle.size() + 1];
    memcpy(buf, new_handle.c_str(), new_handle.size() + 1);
    *handle = buf;
  }
}

void TF_PRun(TF_DeprecatedSession* s, const char* handle,
             // Input tensors

    size_t copy_size = 0;
    if (offset < buffer_end && gcs_file->buffer_start) {
      copy_size = (std::min)(n, static_cast<size_t>(buffer_end - offset));
      memcpy(buffer,
             gcs_file->buffer.data() + (offset - gcs_file->buffer_start),
             copy_size);
    }
    bool consumed_buffer_to_eof =

      TF_RETURN_IF_ERROR(
          tensorflow::XLAShapeToTensorShape(xla_literal->shape(), &shape));
      tensorflow::Tensor tensor(data_type, shape);
      std::memcpy(static_cast<char*>(tensor.data()),
                  xla_literal->untyped_data(),
                  xla::ShapeUtil::ByteSizeOfPrimitiveType(
                      xla_literal->shape().element_type()) *

  OpKernelContext* cc_ctx = reinterpret_cast<OpKernelContext*>(ctx);
  cc_ctx->eigen_gpu_device().memcpyHostToDevice(data, values,
                                                tensor_size_bytes);
#else
  memcpy(data, values, tensor_size_bytes);
#endif
}

    auto status = absl::OkStatus();

    std::vector<uint8_t> custom_options;

    if (IsValidBufferOffset(op.large_custom_options_offset)) {
      custom_options.resize(op.large_custom_options_size);
      memcpy(custom_options.data(),
             reinterpret_cast<const uint8_t*>(model_ptr->allocation()->base()) +
                 op.large_custom_options_offset,
             op.large_custom_options_size);
    } else {

//             [11, 23]]   # == 2nd column in filter
// This is exactly what the EmbeddedLookup operator is doing, on the transposed
// matrix, without doing any arithmetic but only memcpy.
def ReplaceOneHotFullyConnectedWithLookup : Pat<
  (TFL_FullyConnectedOp:$outputs
    (TFL_OneHotOp
      AnyStaticShapeTensor:$indices,
      (Arith_ConstantOp $depth),