debug mindspore hub

mindspore/hub.py

@@ -32,13 +32,12 @@ from mindspore.train.serialization import load_checkpoint, load_param_into_net
 
 DOWNLOAD_BASIC_URL = "http://download.mindspore.cn/model_zoo"
 OFFICIAL_NAME = "official"
-DEFAULT_CACHE_DIR = '~/.cache'
-MODEL_TARGET_CV = ['alexnet', 'fasterrcnn', 'googlenet',
-                   'lenet', 'resnet', 'ssd', 'vgg', 'yolo']
+DEFAULT_CACHE_DIR = '.cache'
+MODEL_TARGET_CV = ['alexnet', 'fasterrcnn', 'googlenet', 'lenet', 'resnet', 'resnet50', 'ssd', 'vgg', 'yolo']
 MODEL_TARGET_NLP = ['bert', 'mass', 'transformer']
 
 
-def _packing_targz(output_filename, savepath="./"):
+def _packing_targz(output_filename, savepath=DEFAULT_CACHE_DIR):
     """
     Packing the input filename to filename.tar.gz in source dir.
     """
@@ -49,7 +48,7 @@ def _packing_targz(output_filename, savepath="./"):
         raise OSError("Cannot tar file {} for - {}".format(output_filename, e))
 
 
-def _unpacking_targz(input_filename, savepath="./"):
+def _unpacking_targz(input_filename, savepath=DEFAULT_CACHE_DIR):
     """
     Unpacking the input filename to dirs.
     """
@@ -69,14 +68,14 @@ def _remove_path_if_exists(path):
 
 
 def _create_path_if_not_exists(path):
-    if os.path.exists(path):
+    if not os.path.exists(path):
         if os.path.isfile(path):
             os.remove(path)
         else:
             os.mkdir(path)
 
 
-def _get_weights_file(url, hash_md5=None, savepath='./'):
+def _get_weights_file(url, hash_md5=None, savepath=DEFAULT_CACHE_DIR):
     """
     get checkpoint weight from giving url.
 
@@ -103,7 +102,8 @@ def _get_weights_file(url, hash_md5=None, savepath='./'):
         download_md5 = m.hexdigest()
         return download_md5 == hash_md5
 
-    _create_path_if_not_exists(savepath)
+    _remove_path_if_exists(os.path.realpath(savepath))
+    _create_path_if_not_exists(os.path.realpath(savepath))
     ckpt_name = os.path.basename(url.split("/")[-1])
     # identify file exist or not
     file_path = os.path.join(savepath, ckpt_name)
@@ -112,8 +112,8 @@ def _get_weights_file(url, hash_md5=None, savepath='./'):
             print('File already exists!')
             return file_path
 
-    file_path = file_path[:-7] if ".tar.gz" in file_path else file_path
-    _remove_path_if_exists(file_path)
+    file_path_ = file_path[:-7] if ".tar.gz" in file_path else file_path
+    _remove_path_if_exists(file_path_)
 
     # download the checkpoint file
     print('Downloading data from url {}'.format(url))
@@ -126,14 +126,12 @@ def _get_weights_file(url, hash_md5=None, savepath='./'):
     print('\nDownload finished!')
 
     # untar file_path
-    _unpacking_targz(file_path)
+    _unpacking_targz(file_path, os.path.realpath(savepath))
 
-    #     # get the file size
-    file_path = os.path.join(savepath, ckpt_name)
     filesize = os.path.getsize(file_path)
     # turn the file size to Mb format
     print('File size = %.2f Mb' % (filesize / 1024 / 1024))
-    return file_path
+    return file_path_
 
 
 def _get_url_paths(url, ext='.tar.gz'):
@@ -150,7 +148,7 @@ def _get_url_paths(url, ext='.tar.gz'):
 
 def _get_file_from_url(base_url, base_name):
     idx = 0
-    urls = _get_url_paths(base_url)
+    urls = _get_url_paths(base_url + "/")
     files = [url.split('/')[-1] for url in urls]
     for i, name in enumerate(files):
         if re.match(base_name + '*', name) is not None:
@@ -172,8 +170,8 @@ def load_weights(network, network_name=None, force_reload=True, **kwargs):
             dataset (string, optional): Dataset to train the network. Default: 'cifar10'.
 
     Example:
-        >>> mindspore.hub.load(network, network_name='lenet',
-                               **{'device_target': 'ascend', 'dataset':'cifar10', 'version': 'beta0.5'})
+        >>> hub.load_weights(network, network_name='lenet',
+                             **{'device_target': 'ascend', 'dataset':'mnist', 'version': '0.5.0'})
     """
     if not isinstance(network, nn.Cell):
         logger.error("Failed to combine the net and the parameters.")
@@ -195,9 +193,11 @@ def load_weights(network, network_name=None, force_reload=True, **kwargs):
         model_type = "cv"
     elif network_name.split("_")[0] in MODEL_TARGET_NLP:
         model_type = "nlp"
+    else:
+        raise ValueError("Unsupported network {} download checkpoint.".format(network_name.split("_")[0]))
 
     download_base_url = "/".join([DOWNLOAD_BASIC_URL,
-                                  OFFICIAL_NAME, model_type])
+                                  OFFICIAL_NAME, model_type, network_name])
     download_file_name = "_".join(
         [network_name, device_target, version, dataset, OFFICIAL_NAME])
     download_url = _get_file_from_url(download_base_url, download_file_name)