Fix

Author: co63oc

ppocr/ext_op/roi_align_rotated/roi_align_rotated.cc

@@ -10,7 +10,7 @@
 
 #define PADDLE_WITH_CUDA
 #define CHECK_INPUT_SAME(x1, x2)                                               \
-  PD_CHECK(x1.place() == x2.place(), "input must be smae pacle.")
+  PD_CHECK(x1.place() == x2.place(), "input must be same place.")
 #define CHECK_INPUT_CPU(x) PD_CHECK(x.is_cpu(), #x " must be a CPU Tensor.")
 
 template <typename T> struct PreCalc {

ppocr/losses/distillation_loss.py

@@ -1026,14 +1026,14 @@ def forward(self, logits_student, logits_teacher, targets, mask=None):
         pred_student = F.softmax(logits_student / self.temperature, axis=-1)
         pred_teacher = F.softmax(logits_teacher / self.temperature, axis=-1)
 
-        # differents with dkd
+        # differences with dkd
         pred_student = paddle.mean(pred_student, axis=1)
         pred_teacher = paddle.mean(pred_teacher, axis=1)
 
         pred_student = self._cat_mask(pred_student, gt_mask, other_mask)
         pred_teacher = self._cat_mask(pred_teacher, gt_mask, other_mask)
 
-        # differents with dkd
+        # differences with dkd
         tckd_loss = self.kl_loss(pred_student, pred_teacher)
 
         gt_mask_ex = paddle.expand_as(gt_mask.unsqueeze(axis=1), logits_teacher)
@@ -1043,11 +1043,11 @@ def forward(self, logits_student, logits_teacher, targets, mask=None):
         pred_student_part2 = F.softmax(
             logits_student / self.temperature - 1000.0 * gt_mask_ex, axis=-1
         )
-        # differents with dkd
+        # differences with dkd
         pred_teacher_part2 = paddle.mean(pred_teacher_part2, axis=1)
         pred_student_part2 = paddle.mean(pred_student_part2, axis=1)
 
-        # differents with dkd
+        # differences with dkd
         nckd_loss = self.kl_loss(pred_student_part2, pred_teacher_part2)
         loss = self.alpha * tckd_loss + self.beta * nckd_loss
         return loss

ppocr/modeling/architectures/base_model.py

@@ -36,7 +36,7 @@ def __init__(self, config):
         model_type = config["model_type"]
         # build transform,
         # for rec, transform can be TPS,None
-        # for det and cls, transform shoule to be None,
+        # for det and cls, transform should to be None,
         # if you make model differently, you can use transform in det and cls
         if "Transform" not in config or config["Transform"] is None:
             self.use_transform = False

ppocr/modeling/backbones/rec_efficientb3_pren.py

@@ -228,7 +228,7 @@ def forward(self, inputs, drop_connect_rate=None):
             x = F.sigmoid(x_squeezed) * x
         x = self._bn2(self._project_conv(x))
 
-        # skip conntection and drop connect
+        # skip connection and drop connect
         if self.id_skip and self._block_args.stride == 1 and self.inp == self.final_oup:
             if drop_connect_rate:
                 x = self._drop_connect(x, p=drop_connect_rate, training=self.training)

ppocr/modeling/backbones/rec_pphgnetv2.py

@@ -521,7 +521,7 @@ def init_net(
                 return_patterns = [stages_pattern[i] for i in return_stages]
 
             if return_patterns:
-                # call update_res function after the __init__ of the object has completed execution, that is, the contructing of layer or model has been completed.
+                # call update_res function after the __init__ of the object has completed execution, that is, the constructing of layer or model has been completed.
                 def update_res_hook(layer, input):
                     self.update_res(return_patterns)
 
@@ -680,7 +680,7 @@ def forward(self, x):
 
         res = self.upgrade_sublayer(layer_name, stop_grad)
         if len(res) == 0:
-            msg = "Failed to stop the gradient befor the layer named '{layer_name}'"
+            msg = "Failed to stop the gradient before the layer named '{layer_name}'"
             return False
         return True
 
@@ -734,12 +734,12 @@ def save_sub_res_hook(layer, input, output):
 def set_identity(
     parent_layer: nn.Layer, layer_name: str, layer_index_list: str = None
 ) -> bool:
-    """set the layer specified by layer_name and layer_index_list to Indentity.
+    """set the layer specified by layer_name and layer_index_list to Identity.
 
     Args:
         parent_layer (nn.Layer): The parent layer of target layer specified by layer_name and layer_index_list.
-        layer_name (str): The name of target layer to be set to Indentity.
-        layer_index_list (str, optional): The index of target layer to be set to Indentity in parent_layer. Defaults to None.
+        layer_name (str): The name of target layer to be set to Identity.
+        layer_index_list (str, optional): The index of target layer to be set to Identity in parent_layer. Defaults to None.
 
     Returns:
         bool: True if successfully, False otherwise.
@@ -775,7 +775,7 @@ def parse_pattern_str(
     """parse the string type pattern.
 
     Args:
-        pattern (str): The pattern to discribe layer.
+        pattern (str): The pattern to describe layer.
         parent_layer (nn.Layer): The root layer relative to the pattern.
 
     Returns:
@@ -806,15 +806,15 @@ def parse_pattern_str(
         target_layer = getattr(parent_layer, target_layer_name, None)
 
         if target_layer is None:
-            msg = f"Not found layer named('{target_layer_name}') specifed in pattern('{pattern}')."
+            msg = f"Not found layer named('{target_layer_name}') specified in pattern('{pattern}')."
             return None
 
         if target_layer_index_list:
             for target_layer_index in target_layer_index_list:
                 if int(target_layer_index) < 0 or int(target_layer_index) >= len(
                     target_layer
                 ):
-                    msg = f"Not found layer by index('{target_layer_index}') specifed in pattern('{pattern}'). The index should < {len(target_layer)} and > 0."
+                    msg = f"Not found layer by index('{target_layer_index}') specified in pattern('{pattern}'). The index should < {len(target_layer)} and > 0."
                     return None
                 target_layer = target_layer[target_layer_index]
 

ppocr/modeling/heads/rec_abinet_head.py

@@ -78,10 +78,10 @@ def forward(self, tokens, lengths):
         embed = self.token_encoder(embed)  # (B, N, C)
         padding_mask = _get_mask(lengths, self.max_length)
         zeros = paddle.zeros_like(embed)  # (B, N, C)
-        qeury = self.pos_encoder(zeros)
+        query = self.pos_encoder(zeros)
         for decoder_layer in self.decoder:
-            qeury = decoder_layer(qeury, embed, cross_mask=padding_mask)
-        output = qeury  # (B, N, C)
+            query = decoder_layer(query, embed, cross_mask=padding_mask)
+        output = query  # (B, N, C)
 
         logits = self.cls(output)  # (B, N, C)
 
@@ -246,7 +246,7 @@ def forward(self, x, targets=None):
                 lengths = align_lengths
                 lengths = paddle.clip(
                     lengths, 2, self.max_length
-                )  # TODO:move to langauge model
+                )  # TODO:move to language model
                 l_feature, l_logits = self.language(tokens, lengths)
 
                 # alignment

ppocr/modeling/heads/rec_aster_head.py

@@ -216,7 +216,7 @@ def _inflate(tensor, times, dim):
             )
             state = paddle.index_select(state, index=predecessors.squeeze(), axis=1)
 
-            # Update sequence socres and erase scores for <eos> symbol so that they aren't expanded
+            # Update sequence scores and erase scores for <eos> symbol so that they aren't expanded
             stored_scores.append(sequence_scores.clone())
             y_prev = paddle.reshape(y_prev, shape=[-1, 1])
             eos_prev = paddle.full_like(y_prev, fill_value=eos)

ppocr/modeling/heads/rec_nrtr_head.py

@@ -23,7 +23,7 @@
 
 
 class Transformer(nn.Layer):
-    """A transformer model. User is able to modify the attributes as needed. The architechture
+    """A transformer model. User is able to modify the attributes as needed. The architecture
     is based on the paper "Attention Is All You Need". Ashish Vaswani, Noam Shazeer,
     Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and
     Illia Polosukhin. 2017. Attention is all you need. In Advances in Neural Information

ppocr/modeling/heads/rec_parseq_head.py

@@ -386,7 +386,7 @@ def forward_test(self, memory, max_length=None):
                 )
                 logits = self.head(tgt_out)
 
-        # transfer to probility
+        # transfer to probability
         logits = F.softmax(logits, axis=-1)
 
         final_output = {"predict": logits}

ppocr/modeling/heads/rec_ppformulanet_head.py

@@ -990,7 +990,7 @@ def _prepare_decoder_input_ids_for_generation(
         if isinstance(decoder_start_token_id, list):
             if len(decoder_start_token_id) != batch_size:
                 raise ValueError(
-                    f"`decoder_start_token_id` expcted to have length {batch_size} but got {len(decoder_start_token_id)}"
+                    f"`decoder_start_token_id` expected to have length {batch_size} but got {len(decoder_start_token_id)}"
                 )
             decoder_input_ids_start = paddle.to_tensor(
                 decoder_start_token_id,