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https://github.com/gradio-app/gradio.git
synced 2024-12-15 02:11:15 +08:00
updated to 0.9.4
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a2276a19df
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@ -31,7 +31,7 @@ class Interface:
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def __init__(self, fn, inputs, outputs, saliency=None, verbose=False, examples=None,
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live=False, show_input=True, show_output=True,
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load_fn=None, capture_session=False, title=None, description=None,
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server_name=LOCALHOST_IP):
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thumbnail=None, server_name=LOCALHOST_IP):
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"""
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:param fn: a function that will process the input panel data from the interface and return the output panel data.
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:param inputs: a string or `AbstractInput` representing the input interface.
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@ -68,8 +68,6 @@ class Interface:
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fn = [fn]
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self.output_interfaces *= len(fn)
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self.predict = fn
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self.load_fn = load_fn
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self.context = None
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self.verbose = verbose
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self.status = "OFF"
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self.saliency = saliency
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@ -82,6 +80,7 @@ class Interface:
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self.server_name = server_name
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self.title = title
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self.description = description
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self.thumbnail = thumbnail
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self.examples = examples
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def get_config_file(self):
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@ -98,31 +97,15 @@ class Interface:
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"show_output": self.show_output,
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"title": self.title,
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"description": self.description,
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"thumbnail": self.thumbnail
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}
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def process(self, raw_input):
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processed_input = [input_interface.preprocess(
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raw_input[i]) for i, input_interface in enumerate(self.input_interfaces)]
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raw_input[i]) for i, input_interface in
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enumerate(self.input_interfaces)]
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predictions = []
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for predict_fn in self.predict:
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if self.context:
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if self.capture_session:
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graph, sess = self.session
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with graph.as_default():
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with sess.as_default():
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prediction = predict_fn(*processed_input,
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self.context)
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else:
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try:
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prediction = predict_fn(*processed_input, self.context)
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except ValueError:
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print("It looks like you might be "
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"using tensorflow < 2.0. Please pass "
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"capture_session=True in Interface to avoid "
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"a 'Tensor is not an element of this graph.' "
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"error.")
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prediction = predict_fn(*processed_input, self.context)
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else:
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if self.capture_session:
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graph, sess = self.session
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with graph.as_default():
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@ -131,13 +114,17 @@ class Interface:
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else:
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try:
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prediction = predict_fn(*processed_input)
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except ValueError:
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print("It looks like you might be "
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"using tensorflow < 2.0. Please pass "
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"capture_session=True in Interface to avoid "
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"a 'Tensor is not an element of this graph.' "
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except ValueError as exception:
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if str(exception).endswith("is not an element of this "
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"graph."):
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raise ValueError("It looks like you might be using "
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"tensorflow < 2.0. Please "
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"pass capture_session=True in "
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"Interface to avoid the 'Tensor is "
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"not an element of this graph.' "
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"error.")
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prediction = predict_fn(*processed_input)
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else:
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raise exception
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if len(self.output_interfaces) / \
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len(self.predict) == 1:
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@ -209,8 +196,6 @@ class Interface:
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"""
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# if validate and not self.validate_flag:
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# self.validate()
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context = self.load_fn() if self.load_fn else None
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self.context = context
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if self.capture_session:
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import tensorflow as tf
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dist/gradio-0.9.4.tar.gz
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dist/gradio-0.9.4.tar.gz
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@ -1,6 +1,6 @@
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Metadata-Version: 1.0
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Name: gradio
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Version: 0.9.3
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Version: 0.9.4
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Summary: Python library for easily interacting with trained machine learning models
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Home-page: https://github.com/abidlabs/gradio
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Author: Abubakar Abid
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@ -2,7 +2,6 @@ MANIFEST.in
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README.md
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setup.py
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gradio/__init__.py
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gradio/hosted.py
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gradio/inputs.py
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gradio/interface.py
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gradio/networking.py
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