unifyai / models Goto Github PK

saving weights and config works fine, but gives this "dump " error while saving the model

model_name = "efficientnet_b0"
​
imported_model1.push_to_huggingface(
repo_id=f"unifyai/{model_name}",
config_path = "config.json",
model_path = "model.pkl",
weights_path = "weights.hdf5",
repo_type = "model",
token = "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",
private = False,
revision = None,
commit_message = "adds {model_name} model",
commit_description = "Adding {model_name} model, config(specs), and weights",
create_pr= False,
safe_serialization = False,
push_config = True,
push_model = True,
push_weights = True,
)

Pushing config to Hugging Face...

TypeError Traceback (most recent call last)
Cell In[19], line 3
1 model_name = "efficientnet_b0"
----> 3 imported_model1.push_to_huggingface(
4 repo_id=f"unifyai/{model_name}",
5 config_path = "config.json",
6 model_path = "model.pkl",
7 weights_path = "weights.hdf5",
8 repo_type = "model",
9 token = "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",
10 private = False,
11 revision = None,
12 commit_message = "adds {model_name} model",
13 commit_description = "Adding {model_name} model, config(specs), and weights",
14 create_pr= False,
15 safe_serialization = False,
16 push_config = True,
17 push_model = True,
18 push_weights = True,
19 )

File /opt/conda/lib/python3.10/site-packages/ivy_models/base/model.py:72, in BaseModel.push_to_huggingface(self, repo_id, config_path, model_path, weights_path, repo_type, token, private, revision, commit_message, commit_description, create_pr, safe_serialization, push_config, push_model, push_weights)
70 if push_config:
71 print("Pushing config to Hugging Face...")
---> 72 self.spec.to_json_file()
73 api.upload_file(
74 path_or_fileobj=config_path,
75 repo_id=repo_id,
76 path_in_repo=config_path,
77 repo_type=repo_type,
78 )
79 os.remove(config_path)

File /opt/conda/lib/python3.10/site-packages/ivy_models/base/spec.py:77, in BaseSpec.to_json_file(self, save_directory)
75 os.makedirs(save_directory, exist_ok=True)
76 with open(os.path.join(save_directory, "config.json"), "w") as f:
---> 77 json.dump(self.dict, f)
78 print("Saved to directory:", save_directory)

File /opt/conda/lib/python3.10/json/init.py:179, in dump(obj, fp, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)
173 iterable = cls(skipkeys=skipkeys, ensure_ascii=ensure_ascii,
174 check_circular=check_circular, allow_nan=allow_nan, indent=indent,
175 separators=separators,
176 default=default, sort_keys=sort_keys, **kw).iterencode(obj)
177 # could accelerate with writelines in some versions of Python, at
178 # a debuggability cost
--> 179 for chunk in iterable:
180 fp.write(chunk)

File /opt/conda/lib/python3.10/json/encoder.py:431, in _make_iterencode.._iterencode(o, _current_indent_level)
429 yield from _iterencode_list(o, _current_indent_level)
430 elif isinstance(o, dict):
--> 431 yield from _iterencode_dict(o, _current_indent_level)
432 else:
433 if markers is not None:

File /opt/conda/lib/python3.10/json/encoder.py:405, in _make_iterencode.._iterencode_dict(dct, _current_indent_level)
403 else:
404 chunks = _iterencode(value, _current_indent_level)
--> 405 yield from chunks
406 if newline_indent is not None:
407 _current_indent_level -= 1

File /opt/conda/lib/python3.10/json/encoder.py:325, in _make_iterencode.._iterencode_list(lst, _current_indent_level)
323 else:
324 chunks = _iterencode(value, _current_indent_level)
--> 325 yield from chunks
326 if newline_indent is not None:
327 _current_indent_level -= 1

File /opt/conda/lib/python3.10/json/encoder.py:438, in _make_iterencode.._iterencode(o, _current_indent_level)
436 raise ValueError("Circular reference detected")
437 markers[markerid] = o
--> 438 o = _default(o)
439 yield from _iterencode(o, _current_indent_level)
440 if markers is not None:

File /opt/conda/lib/python3.10/json/encoder.py:179, in JSONEncoder.default(self, o)
160 def default(self, o):
161 """Implement this method in a subclass such that it returns
162 a serializable object for o, or calls the base implementation
163 (to raise a TypeError).
(...)
177
178 """
--> 179 raise TypeError(f'Object of type {o.class.name} '
180 f'is not JSON serializable')

TypeError: Object of type MBConvConfig is not JSON serializable

These errors are coming on master branch state of the densenet and
after setting batchnorm(training=False), both cases.