message: Fixed an internal bug where width/height were consistently (and incorrectly) mapped to y/x vs the correct x/y.
diff: @@ -684,28 +684,28 @@ OpLevelCostEstimator::ConvolutionDimensionsFromInputs(
  int x_index, y_index, channel_index;
  const string& data_format = GetDataFormat(op_info);
  if (data_format == "NCHW") {
  - x_index = 2;
  - y_index = 3;
  channel_index = 1;
  + y_index = 2;
  + x_index = 3;
  } else {
  // Use NHWC.
  - x_index = 1;
  - y_index = 2;
  + y_index = 1;
  + x_index = 2;
  channel_index = 3;
  }
  const string& filter_format = GetFilterFormat(op_info);
  int filter_x_index, filter_y_index, in_channel_index, out_channel_index;
  if (filter_format == "HWIO") {
  - filter_x_index = 0;
  - filter_y_index = 1;
  + filter_y_index = 0;
  + filter_x_index = 1;
  in_channel_index = 2;
  out_channel_index = 3;
  } else {
  // Use OIHW
  - filter_x_index = 2;
  - filter_y_index = 3;
  - in_channel_index = 1;
  out_channel_index = 0;
  + in_channel_index = 1;
  + filter_y_index = 2;
  + filter_x_index = 3;
  }
  int64 batch = image_shape.dim(0).size();
  int64 ix = image_shape.dim(x_index).size();
  @@ -1311,9 +1311,9 @@ Costs OpLevelCostEstimator::PredictFusedConv2DBiasActivation(
  // TODO(varomodt): should we centralize the Conv2D input/output shapes?
  OpInfo::TensorProperties output;
  if (data_format == "NCHW") {
  - output = DescribeTensor(DT_FLOAT, {dims.batch, dims.oz, dims.ox, dims.oy});
  + output = DescribeTensor(DT_FLOAT, {dims.batch, dims.oz, dims.oy, dims.ox});
  } else if (data_format == "NHWC") {
  - output = DescribeTensor(DT_FLOAT, {dims.batch, dims.ox, dims.oy, dims.oz});
  + output = DescribeTensor(DT_FLOAT, {dims.batch, dims.oy, dims.ox, dims.oz});
  }
  // Add the operations the fused op always computes.
  @@ -1768,12 +1768,12 @@ OpLevelCostEstimator::OpDimensionsFromInputs(
  int x_index, y_index, channel_index;
  const string& data_format = GetDataFormat(op_info);
  if (data_format == "NCHW") {
  - x_index = 2;
  - y_index = 3;
  channel_index = 1;
  - } else {
  - x_index = 1;
  y_index = 2;
  + x_index = 3;
  + } else {
  + y_index = 1;
  + x_index = 2;
  channel_index = 3;
  }
  int64 batch = image_shape.dim(0).size();
  