clould

model_zoo/official/nlp/lstm/config_ascend.yaml

@@ -33,7 +33,7 @@ global_step: 0
 
 # MindSpore LSTM Example - train.py
 preprocess: 'false'
-aclimdb_path: "/cache/data/aclImdb"
+aclimdb_path: "./aclImdb"
 glove_path: "/cache/data"
 preprocess_path: "/cache/train/preprocess"
 ckpt_path: './ckpt_lstm/'

model_zoo/official/nlp/lstm/config_ascend_8p.yaml

@@ -34,7 +34,7 @@ global_step: 0
 
 # MindSpore LSTM Example - train.py
 preprocess: 'false'
-aclimdb_path: "/cache/data/aclImdb"
+aclimdb_path: "./aclImdb"
 glove_path: "/cache/data"
 preprocess_path: "/cache/train/preprocess"
 ckpt_path: './ckpt_lstm/'

model_zoo/official/nlp/lstm/default_config.yaml

@@ -28,7 +28,7 @@ keep_checkpoint_max: 10
 
 # MindSpore LSTM Example - train.py
 preprocess: 'false'
-aclimdb_path: "/cache/data/aclImdb"
+aclimdb_path: "./aclImdb"
 glove_path: "/cache/data"
 preprocess_path: "/cache/train/preprocess"
 ckpt_path: './ckpt_lstm/'

model_zoo/official/nlp/lstm/scripts/run_eval_ascend.sh

@@ -39,6 +39,6 @@ CONFIG_FILE="${BASE_PATH}/../../config_ascend.yaml"
 python ../../eval.py  \
     --config_path=$CONFIG_FILE \
     --device_target="Ascend" \
-    --preprocess=true  \
-    --glove_path=$PREPROCESS_DIR \
+    --preprocess=false \
+    --preprocess_path=$PREPROCESS_DIR \
     --ckpt_file=$CKPT_FILE > log.txt 2>&1 &

model_zoo/official/nlp/lstm/scripts/run_eval_cpu.sh

@@ -37,6 +37,6 @@ python ../eval.py  \
     --device_target="CPU" \
     --aclimdb_path=$ACLIMDB_DIR \
     --glove_path=$GLOVE_DIR \
-    --preprocess=true  \
+    --preprocess=false \
     --preprocess_path=./preprocess \
     --ckpt_file=$CKPT_FILE > log.txt 2>&1 &

model_zoo/official/nlp/lstm/scripts/run_eval_gpu.sh

@@ -40,6 +40,6 @@ python ../eval.py  \
     --device_target="GPU" \
     --aclimdb_path=$ACLIMDB_DIR \
     --glove_path=$GLOVE_DIR \
-    --preprocess=true  \
+    --preprocess=false \
     --preprocess_path=./preprocess \
     --ckpt_file=$CKPT_FILE > log.txt 2>&1 &

model_zoo/official/recommend/wide_and_deep/train_and_eval.py

@@ -104,7 +104,7 @@ def test_train_eval(config):
 
 
 def modelarts_pre_process():
-    config.ckpt_path = config.output_path
+    cfg.ckpt_path = cfg.output_path
 
 @moxing_wrapper(pre_process=modelarts_pre_process)
 def train_wide_and_deep():

model_zoo/official/recommend/wide_and_deep/train_and_eval_auto_parallel.py

@@ -144,7 +144,7 @@ def train_and_eval(config):
 
 
 def modelarts_pre_process():
-    config.ckpt_path = config.output_path
+    cfg.ckpt_path = cfg.output_path
 
 @moxing_wrapper(pre_process=modelarts_pre_process)
 def train_wide_and_deep():

model_zoo/official/recommend/wide_and_deep/train_and_eval_distribute.py

@@ -118,7 +118,7 @@ def train_and_eval(config):
 
 
 def modelarts_pre_process():
-    config.ckpt_path = config.output_path
+    cfg.ckpt_path = cfg.output_path
 
 @moxing_wrapper(pre_process=modelarts_pre_process)
 def train_wide_and_deep():

model_zoo/official/recommend/wide_and_deep/train_and_eval_parameter_server_distribute.py

@@ -145,13 +145,14 @@ def train_and_eval(config):
 
 
 def modelarts_pre_process():
-    config.ckpt_path = config.output_path
+    cfg.ckpt_path = cfg.output_path
+
+context.set_context(mode=context.GRAPH_MODE, device_target=cfg.device_target, save_graphs=True)
+cache_enable = cfg.vocab_cache_size > 0
 
 @moxing_wrapper(pre_process=modelarts_pre_process)
 def train_wide_and_deep():
     """ train_wide_and_deep """
-    context.set_context(mode=context.GRAPH_MODE, device_target=cfg.device_target, save_graphs=True)
-    cache_enable = cfg.vocab_cache_size > 0
     if cache_enable and cfg.device_target != "GPU":
         context.set_context(variable_memory_max_size="24GB")
     context.set_ps_context(enable_ps=True)

model_zoo/official/recommend/wide_and_deep/train_and_eval_parameter_server_standalone.py

@@ -117,13 +117,14 @@ def train_and_eval(config):
 
 
 def modelarts_pre_process():
-    config.ckpt_path = config.output_path
+    cfg.ckpt_path = cfg.output_path
+
+context.set_context(mode=context.GRAPH_MODE, device_target=cfg.device_target, save_graphs=True)
+cache_enable = cfg.vocab_cache_size > 0
 
 @moxing_wrapper(pre_process=modelarts_pre_process)
 def train_wide_and_deep():
     """ train_wide_and_deep """
-    context.set_context(mode=context.GRAPH_MODE, device_target=cfg.device_target, save_graphs=True)
-    cache_enable = cfg.vocab_cache_size > 0
     if not cache_enable:
         cfg.sparse = True
     if cfg.sparse: