[CodeStyle][Typos][E[1-3],F[1-2]] Fix typo(effec,embeder,emebedding,fale,functinal)

paddle/cinn/hlir/dialect/operator/transforms/add_cinn_pass.cc

@@ -37,7 +37,7 @@
 #include "paddle/cinn/hlir/dialect/operator/transforms/cinn_group_cluster_pass.h"
 #include "paddle/cinn/hlir/dialect/operator/transforms/conv2d_transpose_filter_pass.h"
 #include "paddle/cinn/hlir/dialect/operator/transforms/convert_fa_to_qkvmha_pass.h"
-#include "paddle/cinn/hlir/dialect/operator/transforms/convert_memory_effec_attn_to_flash_attn_pass.h"
+#include "paddle/cinn/hlir/dialect/operator/transforms/convert_memory_effect_attn_to_flash_attn_pass.h"
 #include "paddle/cinn/hlir/dialect/operator/transforms/dynamic_reshape_pass.h"
 #include "paddle/cinn/hlir/dialect/operator/transforms/fold_full_pass.h"
 #include "paddle/cinn/hlir/dialect/operator/transforms/fold_manipulation_ops_pass.h"

paddle/cinn/hlir/dialect/operator/transforms/convert_memory_effec_attn_to_flash_attn_pass.cc → paddle/cinn/hlir/dialect/operator/transforms/convert_memory_effect_attn_to_flash_attn_pass.cc

@@ -12,7 +12,7 @@
 // See the License for the specific language governing permissions and
 // limitations under the License.
 
-#include "paddle/cinn/hlir/dialect/operator/transforms/convert_memory_effec_attn_to_flash_attn_pass.h"
+#include "paddle/cinn/hlir/dialect/operator/transforms/convert_memory_effect_attn_to_flash_attn_pass.h"
 
 #include "paddle/cinn/hlir/dialect/operator/ir/cinn_op.h"
 #include "paddle/cinn/hlir/dialect/operator/ir/manual_op.h"

python/paddle/distributed/passes/auto_parallel_c_embedding.py

@@ -87,7 +87,7 @@ def _update_weight(self, op, concrete_program):
             op.operand(1).source().type(), dist_attr_w
         )
         op.operand(1).source().set_type(dist_type_input0)
-        # update c_emebedding weight dynamic parameters
+        # update c_embedding weight dynamic parameters
         dy_params = concrete_program.parameters[0]
         pattern = re.compile(r'embedding_.*\.w_0\.dist')
         for index, param in enumerate(dy_params):

python/paddle/nn/decode.py

@@ -201,14 +201,14 @@ class BeamSearchDecoder(Decoder):
             >>> import paddle
             >>> from paddle.nn import BeamSearchDecoder, dynamic_decode
             >>> from paddle.nn import GRUCell, Linear, Embedding
-            >>> trg_embeder = Embedding(100, 32)
+            >>> trg_embedder = Embedding(100, 32)
             >>> output_layer = Linear(32, 32)
             >>> decoder_cell = GRUCell(input_size=32, hidden_size=32)
             >>> decoder = BeamSearchDecoder(decoder_cell,
             ...                             start_token=0,
             ...                             end_token=1,
             ...                             beam_size=4,
-            ...                             embedding_fn=trg_embeder,
+            ...                             embedding_fn=trg_embedder,
             ...                             output_fn=output_layer)
             ...
     """
@@ -1342,14 +1342,14 @@ def dynamic_decode(
             >>> import paddle
             >>> from paddle.nn import BeamSearchDecoder, dynamic_decode
             >>> from paddle.nn import GRUCell, Linear, Embedding
-            >>> trg_embeder = Embedding(100, 32)
+            >>> trg_embedder = Embedding(100, 32)
             >>> output_layer = Linear(32, 32)
             >>> decoder_cell = GRUCell(input_size=32, hidden_size=32)
             >>> decoder = BeamSearchDecoder(decoder_cell,
             ...                             start_token=0,
             ...                             end_token=1,
             ...                             beam_size=4,
-            ...                             embedding_fn=trg_embeder,
+            ...                             embedding_fn=trg_embedder,
             ...                             output_fn=output_layer)
             >>> encoder_output = paddle.ones((4, 8, 32), dtype=paddle.get_default_dtype())
             >>> outputs = dynamic_decode(decoder=decoder,

test/dygraph_to_static/seq2seq_dygraph_model.py

@@ -114,15 +114,15 @@ def __init__(
         bias_attr = paddle.ParamAttr(initializer=zero_constant)
         forget_bias = 1.0
 
-        self.src_embeder = Embedding(
+        self.src_embedder = Embedding(
             self.src_vocab_size,
             self.hidden_size,
             weight_attr=paddle.ParamAttr(
                 initializer=uniform_initializer(init_scale)
             ),
         )
 
-        self.tar_embeder = Embedding(
+        self.tar_embedder = Embedding(
             self.tar_vocab_size,
             self.hidden_size,
             sparse=False,
@@ -205,7 +205,7 @@ def forward(self, inputs):
         if src.shape[0] < self.batch_size:
             self.batch_size = src.shape[0]
 
-        src_emb = self.src_embeder(self._transpose_batch_time(src))
+        src_emb = self.src_embedder(self._transpose_batch_time(src))
 
         # NOTE: modify model code about `enc_hidden` and `enc_cell` to transform dygraph code successfully.
         # Because nested list can't be transformed now.
@@ -265,7 +265,7 @@ def forward(self, inputs):
             enc_hidden, enc_cell = new_enc_hidden, new_enc_cell
 
         dec_hidden, dec_cell = enc_hidden, enc_cell
-        tar_emb = self.tar_embeder(self._transpose_batch_time(tar))
+        tar_emb = self.tar_embedder(self._transpose_batch_time(tar))
         max_seq_len = tar_emb.shape[0]
         dec_output = []
         for step_idx in range(max_seq_len):
@@ -309,7 +309,7 @@ def beam_search(self, inputs):
         if src.shape[0] < self.batch_size:
             self.batch_size = src.shape[0]
 
-        src_emb = self.src_embeder(self._transpose_batch_time(src))
+        src_emb = self.src_embedder(self._transpose_batch_time(src))
         enc_hidden_0 = paddle.zeros(
             shape=[self.batch_size, self.hidden_size], dtype='float32'
         )
@@ -372,7 +372,7 @@ def beam_search(self, inputs):
         end_token_tensor = paddle.full(
             batch_beam_shape, self.beam_end_token, dtype="int64"
         )
-        step_input = self.tar_embeder(start_token_tensor)
+        step_input = self.tar_embedder(start_token_tensor)
         beam_finished = paddle.full(batch_beam_shape, 0, dtype="float32")
         beam_state_log_probs = paddle.to_tensor(
             [[0.0] + [-self.kinf] * (self.beam_size - 1)], dtype="float32"
@@ -482,7 +482,7 @@ def beam_search(self, inputs):
             dec_hidden, dec_cell = new_dec_hidden, new_dec_cell
             beam_finished = next_finished
             beam_state_log_probs = next_log_probs
-            step_input = self.tar_embeder(token_indices)
+            step_input = self.tar_embedder(token_indices)
             predicted_ids.append(token_indices)
             parent_ids.append(beam_indices)
 
@@ -532,7 +532,7 @@ def __init__(
         bias_attr = paddle.ParamAttr(initializer=zero_constant)
         forget_bias = 1.0
 
-        self.src_embeder = Embedding(
+        self.src_embedder = Embedding(
             self.src_vocab_size,
             self.hidden_size,
             weight_attr=paddle.ParamAttr(
@@ -541,7 +541,7 @@ def __init__(
             ),
         )
 
-        self.tar_embeder = Embedding(
+        self.tar_embedder = Embedding(
             self.tar_vocab_size,
             self.hidden_size,
             sparse=False,
@@ -713,7 +713,7 @@ def forward(self, inputs):
         if src.shape[0] < self.batch_size:
             self.batch_size = src.shape[0]
 
-        src_emb = self.src_embeder(self._transpose_batch_time(src))
+        src_emb = self.src_embedder(self._transpose_batch_time(src))
 
         # NOTE: modify model code about `enc_hidden` and `enc_cell` to transform dygraph code successfully.
         # Because nested list can't be transformed now.
@@ -786,7 +786,7 @@ def forward(self, inputs):
         # NOTE: set stop_gradient here, otherwise grad var is null
         input_feed.stop_gradient = True
         dec_hidden, dec_cell = enc_hidden, enc_cell
-        tar_emb = self.tar_embeder(self._transpose_batch_time(tar))
+        tar_emb = self.tar_embedder(self._transpose_batch_time(tar))
         max_seq_len = tar_emb.shape[0]
         dec_output = []
 

test/legacy_test/test_fleet_rolemaker_2.py

@@ -194,7 +194,7 @@ def all_reduce_worker(self, input, output):
 
                 Args:
                     input(None): fake input
-                    output(None): fale output
+                    output(None): fake output
                 """
                 pass
 

test/legacy_test/test_warprnnt_op.py

@@ -449,7 +449,7 @@ def config(self):
             dtype=np.float64,
         )
 
-    def test_functinal_api(self):
+    def test_functional_api(self):
         self.config()
 
         paddle.disable_static()