blob: bb5d8d3390b03a66d88902cdab7ddb9891b47ac7 [file] [log] [blame]
// Copyright 2020 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
#include <assert.h>
#include <stddef.h>
#include <stdint.h>
#include <stdlib.h>
#include <xnnpack.h>
#include <xnnpack/allocator.h>
#include <xnnpack/log.h>
#include <xnnpack/params.h>
#include <xnnpack/subgraph.h>
enum xnn_status xnn_define_tensor_value(
xnn_subgraph_t subgraph,
enum xnn_datatype datatype,
size_t num_dims,
const size_t* dims,
const void* data,
uint32_t external_id,
uint32_t flags,
uint32_t* id_out)
{
if ((xnn_params.init_flags & XNN_INIT_FLAG_XNNPACK) == 0) {
xnn_log_error("failed to create Dense Tensor value: XNNPACK is not initialized");
return xnn_status_uninitialized;
}
if (external_id != XNN_INVALID_VALUE_ID && external_id >= subgraph->external_value_ids) {
xnn_log_error(
"failed to create Dense Tensor value: "
"external ID %" PRIu32 " exceeds the number of reserved external IDs in subgraph (%" PRIu32 ")",
external_id, subgraph->external_value_ids);
return xnn_status_invalid_parameter;
}
if (num_dims > XNN_MAX_TENSOR_DIMS) {
xnn_log_error("failed to create Dense Tensor value: num of dimensions exceeds XNNPACK limit (%d)",
XNN_MAX_TENSOR_DIMS);
return xnn_status_unsupported_parameter;
}
switch (datatype) {
case xnn_datatype_fp32:
case xnn_datatype_fp16:
break;
default:
xnn_log_error("failed to create Dense Tensor value: invalid data type (%d)", datatype);
return xnn_status_unsupported_parameter;
}
struct xnn_value* value = subgraph->values + external_id;
if (external_id == XNN_INVALID_VALUE_ID) {
value = xnn_subgraph_new_internal_value(subgraph);
if (value == NULL) {
return xnn_status_out_of_memory;
}
}
value->type = xnn_value_type_dense_tensor;
value->datatype = datatype;
value->shape.num_dims = num_dims;
memcpy(value->shape.dim, dims, num_dims * sizeof(size_t));
value->flags = flags;
value->data = data;
*id_out = value->id;
return xnn_status_success;
}
size_t xnn_tensor_get_size(
xnn_subgraph_t subgraph,
uint32_t value_id)
{
assert(value_id < subgraph->num_values);
const struct xnn_value* value = subgraph->values + value_id;
assert(value->type == xnn_value_type_dense_tensor);
assert(value->datatype != xnn_datatype_invalid);
size_t size = 0;
switch (value->datatype) {
case xnn_datatype_fp16:
size = 2;
break;
case xnn_datatype_fp32:
size = 4;
break;
case xnn_datatype_invalid:
XNN_UNREACHABLE;
}
for (size_t i = 0; i < value->shape.num_dims; i++) {
size *= value->shape.dim[i];
}
return size;
}