| // 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; |
| } |