remove modelzoo some warnings

official/cv/cspdarknet53/src/utils/var_init.py

@@ -121,14 +121,14 @@ def default_recurisive_init(custom_cell):
     for _, cell in custom_cell.cells_and_names():
         if isinstance(cell, nn.Conv2d):
             cell.weight.set_data(init.initializer(KaimingUniform(a=math.sqrt(5.0)), cell.weight.data.shape,
-                                                  cell.weight.data.dtype).to_tensor())
+                                                  cell.weight.data.dtype).init_data())
             if cell.bias is not None:
                 fan_in, _ = _calculate_in_and_out(cell.weight.data.asnumpy())
                 bound = 1 / math.sqrt(fan_in)
                 cell.bias.set_data(Tensor(np.random.uniform(-bound, bound, cell.bias.data.shape), cell.bias.data.dtype))
         elif isinstance(cell, nn.Dense):
             cell.weight.set_data(init.initializer(KaimingUniform(a=math.sqrt(5)), cell.weight.data.shape,
-                                                  cell.weight.data.dtype).to_tensor())
+                                                  cell.weight.data.dtype).init_data())
             if cell.bias is not None:
                 fan_in, _ = _calculate_in_and_out(cell.weight.data.asnumpy())
                 bound = 1 / math.sqrt(fan_in)

official/nlp/fasttext/README.md

@@ -68,9 +68,6 @@ After dataset preparation, you can start training and evaluation as follows:
     cd ./scripts
     bash run_standalone_train.sh [TRAIN_DATASET] [DEVICEID] [DATANAME]
 
-    # run distributed training example
-    bash run_distribute_train.sh [TRAIN_DATASET] [RANK_TABLE_PATH] [DATANAME]
-
     # run evaluation example
     bash run_eval.sh [EVAL_DATASET_PATH] [DATASET_NAME] [MODEL_CKPT] [DEVICEID]
     ```
@@ -220,13 +217,6 @@ Parameters for both training and evaluation can be set in config.py. All the dat
         bash run_standalone_train.sh [DATASET_PATH] [DEVICE_ID] [DATANAME]
         ```
 
-    - Running scripts for distributed training of FastText. Task training on multiple device and run the following command in bash to be executed in `scripts/`:
-
-        ```bash
-        cd ./scripts
-        bash run_distributed_train.sh [DATASET_PATH] [RANK_TABLE_PATH] [DATANAME]
-        ```
-
 - Running on GPU
 
     - Start task training on a single device and run the shell script

official/nlp/fasttext/scripts/run_distribute_train_8p.sh

-#!/bin/bash
-# Copyright 2020 Huawei Technologies Co., Ltd
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ============================================================================
-
-echo "=============================================================================================================="
-echo "Please run the script as: "
-echo "sh run_distributed_train.sh DATASET_PATH RANK_TABLE_PATH"
-echo "for example: sh run_distributed_train.sh /home/workspace/ag /home/workspace/rank_table_file.json ag"
-echo "It is better to use absolute path."
-echo "Please pay attention that the dataset should corresponds to dataset_name"
-echo "=============================================================================================================="
-get_real_path(){
-  if [ "${1:0:1}" == "/" ]; then
-    echo "$1"
-  else
-    echo "$(realpath -m $PWD/$1)"
-  fi
-}
-
-if [ $3 != "ag" ] && [ $3 != "dbpedia" ] && [ $3 != "yelp_p" ]
-then
-  echo "Unrecognized dataset name, the name can choose from [ag, dbpedia, yelp_p]"
-exit 1
-fi
-
-DATASET=$(get_real_path $1)
-echo $DATASET
-RANK_TABLE_PATH=$(get_real_path $2)
-if [ ! -d $DATASET ]
-then
-  echo "Error: DATA_PATH=$DATASET is not a file"
-exit 1
-fi
-current_exec_path=$(pwd)
-echo ${current_exec_path}
-
-export RANK_TABLE_FILE=$RANK_TABLE_PATH
-
-
-echo $RANK_TABLE_FILE
-export RANK_SIZE=8
-export DEVICE_NUM=8
-
-if [ $# -ge 1 ]; then
-  if [ $3 == 'ag' ]; then
-    DATANAME='ag'
-  elif [ $3 == 'dbpedia' ]; then
-    DATANAME='dbpedia'
-  elif [ $3 == 'yelp_p' ]; then
-    DATANAME='yelp_p'
-  else
-    echo "Unrecognized dataset name,he name can choose from [ag, dbpedia, yelp_p]"
-    exit 1
-  fi
-fi
-
-config_path="./${DATANAME}_config.yaml"
-echo "config path is : ${config_path}"
-
-for((i=0;i<=7;i++));
-do
-    rm -rf ${current_exec_path}/device$i
-    mkdir ${current_exec_path}/device$i
-    cd ${current_exec_path}/device$i || exit
-    cp ../../*.py ./
-    cp ../../*.yaml ./
-    cp -r ../../src ./
-    cp -r ../../model_utils ./
-    cp -r ../*.sh ./
-    export RANK_ID=$i
-    export DEVICE_ID=$i
-    echo "start training for rank $i, device $DEVICE_ID"
-    python ../../train.py --config_path $config_path --dataset_path $DATASET --data_name $DATANAME > log_fasttext.log 2>&1 &
-    cd ${current_exec_path} || exit
-done
-cd ${current_exec_path} || exit

official/recommend/wide_and_deep/train_and_eval.py

@@ -113,7 +113,6 @@ def train_wide_and_deep():
                         enable_graph_kernel=_enable_graph_kernel, device_target=cfg.device_target)
     if _enable_graph_kernel:
         context.set_context(graph_kernel_flags="--enable_cluster_ops=MatMul")
-    context.set_context(enable_sparse=cfg.sparse)
     test_train_eval(cfg)
 
 if __name__ == "__main__":

official/recommend/wide_and_deep/train_and_eval_auto_parallel.py

@@ -154,7 +154,6 @@ def train_wide_and_deep():
     if cfg.device_target == "GPU":
         context.set_context(enable_graph_kernel=True)
     context.set_context(variable_memory_max_size="24GB")
-    context.set_context(enable_sparse=True)
     init()
     context.set_context(save_graphs_path='./graphs_of_device_id_' + str(get_rank()), save_graphs=True)
     if cfg.sparse:

official/recommend/wide_and_deep/train_and_eval_distribute.py

@@ -130,7 +130,6 @@ def train_wide_and_deep():
         context.set_context(enable_graph_kernel=True)
         context.set_context(graph_kernel_flags="--enable_cluster_ops=MatMul")
 
-    context.set_context(enable_sparse=cfg.sparse)
     init()
     context.set_context(save_graphs_path='./graphs_of_device_id_'+str(get_rank()))
     context.set_auto_parallel_context(parallel_mode=ParallelMode.DATA_PARALLEL, gradients_mean=True,

official/recommend/wide_and_deep/train_and_eval_parameter_server_distribute.py

@@ -167,8 +167,6 @@ def train_wide_and_deep():
                                           device_num=get_group_size())
         cfg.sparse = True
 
-    if cfg.sparse:
-        context.set_context(enable_sparse=True)
     if cfg.device_target == "GPU":
         context.set_context(enable_graph_kernel=True)
         context.set_context(graph_kernel_flags="--enable_cluster_ops=MatMul")

official/recommend/wide_and_deep/train_and_eval_parameter_server_standalone.py

@@ -127,8 +127,6 @@ def train_wide_and_deep():
     """ train_wide_and_deep """
     if not cache_enable:
         cfg.sparse = True
-    if cfg.sparse:
-        context.set_context(enable_sparse=True)
     if cfg.device_target == "GPU":
         context.set_context(enable_graph_kernel=True)
         context.set_context(graph_kernel_flags="--enable_cluster_ops=MatMul")