310p export bug fix

mindocr/models/backbones/rec_svtr.py

@@ -473,7 +473,9 @@ def __init__(
 
  if use_pos_embed:
  self.pos_embed = Parameter(
- ops.zeros((1, num_patches, embed_dim[0]), ms.float32)
+ Tensor(
+ np.zeros((1, num_patches, embed_dim[0]), np.float32), dtype=ms.float32
+ )
  )
  else:
  self.pos_embed = None

mindocr/models/transforms/stn.py

@@ -70,8 +70,7 @@ def init_stn(self) -> Tensor:
  pass
  elif self.activation == "sigmoid":
  ctrl_points = -np.log(1.0 / ctrl_points - 1.0)
- ctrl_points = Tensor(ctrl_points)
- fc2_bias = ops.reshape(ctrl_points, (-1,))
+ fc2_bias = Tensor(np.reshape(ctrl_points, (-1,)))
  return fc2_bias
 
  def construct(self, x: Tensor) -> Tuple[Tensor, Tensor]:

mindocr/models/transforms/tps_spatial_transformer.py

@@ -108,7 +108,7 @@ def __init__(
 
  # register precomputed matrices
  self.inverse_kernel = Tensor(inverse_kernel, dtype=ms.float32)
- self.padding_matrix = ops.zeros((1, 3, 2), ms.float32)
+ self.padding_matrix = Tensor(np.zeros((1, 3, 2), np.float32), dtype=ms.float32)
  self.target_coordinate_repr = Tensor(target_coordinate_repr, dtype=ms.float32)
  self.target_control_points = Tensor(target_control_points, dtype=ms.float32)
 
@@ -119,8 +119,8 @@ def construct(
 
  padding_matrix = ops.tile(self.padding_matrix, (batch_size, 1, 1))
  Y = ops.concat([source_control_points, padding_matrix], axis=1)
- mapping_matrix = ops.matmul(self.inverse_kernel, Y)
- source_coordinate = ops.matmul(self.target_coordinate_repr, mapping_matrix)
+ mapping_matrix = ops.matmul(self.inverse_kernel.expand_dims(0), Y)
+ source_coordinate = ops.matmul(self.target_coordinate_repr.expand_dims(0), mapping_matrix)
  grid = ops.reshape(
  source_coordinate,
  (-1, self.target_height, self.target_width, 2),

mindocr/models/utils/abinet_layers.py

@@ -342,8 +342,8 @@ def __init__(self, d_model=512, dropout=0.9, max_len=5000):
  pe[:, 0::2] = np.sin(position * div_term)
  pe[:, 1::2] = np.cos(position * div_term)
  pe = np.expand_dims(pe, 0)
+ pe = np.transpose(pe, (1, 0, 2))
  pe = ms.Tensor(pe).astype(dtype=ms.float32)
- pe = pe.transpose(1, 0, 2)
  self.pe = ms.Parameter(pe, name="pe1", requires_grad=False)
 
  def construct(self, x):

tools/data_for_export_convert.py

@@ -411,7 +411,7 @@
  "master_resnet31": {"model_name": "master_resnet31", "data_shape_h_w": [32, 100]},
  "cls_mobilenet_v3_small_100_model": {"model_name": "cls_mobilenet_v3_small_100_model", "data_shape_h_w": [48, 192]},
  "crnn_resnet34": {"model_name": "crnn_resnet34", "data_shape_h_w": [32, 100]},
- "crnn_resnet34_ch": {"model_name": "crnn_resnet34_ch", "data_shape_h_w": [32, 100]},
+ "crnn_resnet34_ch": {"model_name": "crnn_resnet34_ch", "data_shape_h_w": [32, 320]},
  "crnn_vgg7": {"model_name": "crnn_vgg7", "data_shape_h_w": [32, 100]},
  "dbnet_mobilenetv3": {"model_name": "dbnet_mobilenetv3", "data_shape_h_w": [736, 1280]},
  "dbnet_resnet18": {"model_name": "dbnet_resnet18", "data_shape_h_w": [736, 1280]},

tools/export_convert_tool.py

@@ -77,7 +77,7 @@ def convert_mindir(self, model, info, input_file, config_file, force=False):
  else:
  log = f"{converted_model_path}.mindir exists and it will be overwritten if exported successfully."
  subprocess.call(f"echo {log}".split(), stdout=self.log_handle, stderr=self.log_handle)
- os.remove(converted_model_path)
+ os.remove(f"{converted_model_path}.mindir")
  print(log)
  command = (
  f"{self.convert_tool} --fmk=MINDIR --modelFile={input_file} --outputFile={converted_model_path}"