src/subgraph/leaky-relu.c

// 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 <math.h>
#include <stddef.h>
#include <stdint.h>

#include <xnnpack.h>
#include <xnnpack/log.h>
#include <xnnpack/params.h>
#include <xnnpack/subgraph.h>


static enum xnn_status create_leaky_relu_operator(
  const struct xnn_node* node,
  const struct xnn_value* values,
  size_t num_values,
  struct xnn_operator_data* opdata)
{
  assert(node->num_inputs == 1);
  const uint32_t input_id = node->inputs[0];
  assert(input_id != XNN_INVALID_VALUE_ID);
  assert(input_id < num_values);

  assert(node->num_outputs == 1);
  const uint32_t output_id = node->outputs[0];
  assert(output_id != XNN_INVALID_VALUE_ID);
  assert(output_id < num_values);

  const size_t num_input_dims = values[input_id].shape.num_dims;
  const size_t channel_dim = num_input_dims == 0 ? 1 : values[input_id].shape.dim[num_input_dims - 1];

  enum xnn_status status = xnn_create_leaky_relu_nc_f32(
    channel_dim /* channels */, channel_dim /* input stride */, channel_dim /* output stride */,
    node->params.leaky_relu.negative_slope,
    node->flags,
    &opdata->operator_object);
  if (status == xnn_status_success) {
    opdata->batch_size = xnn_shape_multiply_non_channel_dims(&values[input_id].shape);
    opdata->inputs[0] = input_id;
    opdata->outputs[0] = output_id;
  }
  return status;
}

static enum xnn_status setup_leaky_relu_operator(
  const struct xnn_operator_data* opdata,
  const struct xnn_blob* blobs,
  size_t num_blobs,
  pthreadpool_t threadpool)
{
  const uint32_t input_id = opdata->inputs[0];
  assert(input_id != XNN_INVALID_VALUE_ID);
  assert(input_id < num_blobs);

  const uint32_t output_id = opdata->outputs[0];
  assert(output_id != XNN_INVALID_VALUE_ID);
  assert(output_id < num_blobs);

  const struct xnn_blob* input_blob = blobs + input_id;
  const void* input_data = input_blob->data;
  assert(input_data != NULL);

  const struct xnn_blob* output_blob = blobs + output_id;
  void* output_data = output_blob->data;
  assert(output_data != NULL);

  return xnn_setup_leaky_relu_nc_f32(
    opdata->operator_object,
    opdata->batch_size,
    input_data,
    output_data,
    threadpool);
}

enum xnn_status xnn_define_leaky_relu(
  xnn_subgraph_t subgraph,
  float negative_slope,
  uint32_t input_id,
  uint32_t output_id,
  uint32_t flags)
{
  if ((xnn_params.init_flags & XNN_INIT_FLAG_XNNPACK) == 0) {
    xnn_log_error("failed to define %s operator: XNNPACK is not initialized",
      xnn_node_type_to_string(xnn_node_type_leaky_relu));
    return xnn_status_uninitialized;
  }

  if (!isfinite(negative_slope)) {
    xnn_log_error(
      "failed to create %s operator with %f negative slope: finite number expected",
      xnn_node_type_to_string(xnn_node_type_leaky_relu),
      negative_slope);
    return xnn_status_invalid_parameter;
  }

  if (input_id >= subgraph->num_values) {
    xnn_log_error(
      "failed to define %s operator with input ID #%" PRIu32 ": invalid Value ID",
      xnn_node_type_to_string(xnn_node_type_leaky_relu), input_id);
    return xnn_status_invalid_parameter;
  }

  const struct xnn_value* input_value = &subgraph->values[input_id];
  if (input_value->type != xnn_value_type_dense_tensor) {
    xnn_log_error(
      "failed to define %s operator with input ID #%" PRIu32 ": unsupported Value type %d (expected dense tensor)",
      xnn_node_type_to_string(xnn_node_type_leaky_relu), input_id, input_value->type);
    return xnn_status_invalid_parameter;
  }

  switch (input_value->datatype) {
    case xnn_datatype_fp32:
      break;
    default:
      xnn_log_error(
        "failed to define %s operator with input ID #%" PRIu32 ": unsupported Value datatype %s (%d)",
        xnn_node_type_to_string(xnn_node_type_leaky_relu), input_id,
        xnn_datatype_to_string(input_value->datatype), input_value->datatype);
      return xnn_status_invalid_parameter;
  }

  if (output_id >= subgraph->num_values) {
    xnn_log_error(
      "failed to define %s operator with output ID #%" PRIu32 ": invalid Value ID",
      xnn_node_type_to_string(xnn_node_type_leaky_relu), output_id);
    return xnn_status_invalid_parameter;
  }

  const struct xnn_value* output_value = &subgraph->values[output_id];
  if (output_value->type != xnn_value_type_dense_tensor) {
    xnn_log_error(
      "failed to define %s operator with output ID #%" PRIu32 ": unsupported Value type %d (expected dense tensor)",
      xnn_node_type_to_string(xnn_node_type_leaky_relu), output_id, output_value->type);
    return xnn_status_invalid_parameter;
  }

  switch (output_value->datatype) {
    case xnn_datatype_fp32:
      break;
    default:
      xnn_log_error(
        "failed to define %s operator with output ID #%" PRIu32 ": unsupported Value datatype %s (%d)",
        xnn_node_type_to_string(xnn_node_type_leaky_relu), output_id,
        xnn_datatype_to_string(output_value->datatype), output_value->datatype);
      return xnn_status_invalid_parameter;
  }

  struct xnn_node* node = xnn_subgraph_new_node(subgraph);
  if (node == NULL) {
    return xnn_status_out_of_memory;
  }

  node->type = xnn_node_type_leaky_relu;
  node->params.leaky_relu.negative_slope = negative_slope;
  node->num_inputs = 1;
  node->inputs[0] = input_id;
  node->num_outputs = 1;
  node->outputs[0] = output_id;
  node->flags = flags;

  node->create = create_leaky_relu_operator;
  node->setup = setup_leaky_relu_operator;

  return xnn_status_success;
}