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updated PyPi version

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This commit is contained in:
Abubakar Abid 2020-08-31 10:07:45 -05:00
parent 8af47c4321
commit b9afa17023
7 changed files with 60 additions and 23 deletions
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46
build/lib/gradio/inputs.py
View File

@ -15,17 +15,19 @@ import base64
import numpy as np
import PIL
import scipy.io.wavfile
from gradio import processing_utils
from gradio import processing_utils, test_data
import pandas as pd
import math
import tempfile
class InputComponent(Component):
"""
Input Component. All input components subclass this.
"""
pass
class Textbox(InputComponent):
"""
Component creates a textbox for user to enter input. Provides a string (or number is `type` is "float") as an argument to the wrapped function.
@ -33,7 +35,7 @@ class Textbox(InputComponent):
"""
def __init__(self, lines=1, placeholder=None, default=None, numeric=False, type="str", label=None):
'''
"""
Parameters:
lines (int): number of line rows to provide in textarea.
placeholder (str): placeholder hint to provide behind textarea.
@ -41,7 +43,7 @@ class Textbox(InputComponent):
numeric (bool): DEPRECATED. Whether the input should be parsed as a number instead of a string.
type (str): Type of value to be returned by component. "str" returns a string, "number" returns a float value.
label (str): component name in interface.
'''
"""
self.lines = lines
self.placeholder = placeholder
self.default = default
@ -50,6 +52,13 @@ class Textbox(InputComponent):
self.type = "number"
else:
self.type = type
if default is None:
self.test_input = {
"str": "the quick brown fox jumped over the lazy dog",
"number": 786.92,
}[type]
else:
self.test_input = default
super().__init__(label)
def get_template_context(self):
@ -77,7 +86,6 @@ class Textbox(InputComponent):
raise ValueError("Unknown type: " + self.type + ". Please choose from: 'str', 'number'.")
class Slider(InputComponent):
"""
Component creates a slider that ranges from `minimum` to `maximum`. Provides a number as an argument to the wrapped function.
@ -101,6 +109,7 @@ class Slider(InputComponent):
step = 10 ** power
self.step = step
self.default = minimum if default is None else default
self.test_input = self.default
super().__init__(label)
def get_template_context(self):
@ -126,10 +135,11 @@ class Checkbox(InputComponent):
"""
def __init__(self, label=None):
'''
"""
Parameters:
label (str): component name in interface.
'''
"""
self.test_input = True
super().__init__(label)
@classmethod
@ -154,6 +164,7 @@ class CheckboxGroup(InputComponent):
'''
self.choices = choices
self.type = type
self.test_input = self.choices
super().__init__(label)
def get_template_context(self):
@ -186,6 +197,7 @@ class Radio(InputComponent):
'''
self.choices = choices
self.type = type
self.test_input = self.choices[0]
super().__init__(label)
def get_template_context(self):
@ -202,6 +214,7 @@ class Radio(InputComponent):
else:
raise ValueError("Unknown type: " + self.type + ". Please choose from: 'value', 'index'.")
class Dropdown(InputComponent):
"""
Component creates a dropdown of which only one can be selected. Provides string representing selected choice as an argument to the wrapped function.
@ -217,6 +230,7 @@ class Dropdown(InputComponent):
'''
self.choices = choices
self.type = type
self.test_input = self.choices[0]
super().__init__(label)
def get_template_context(self):
@ -248,7 +262,7 @@ class Image(InputComponent):
invert_colors (bool): whether to invert the image as a preprocessing step.
source (str): Source of image. "upload" creates a box where user can drop an image file, "webcam" allows user to take snapshot from their webcam, "canvas" defaults to a white image that can be edited and drawn upon with tools.
tool (str): Tools used for editing. "editor" allows a full screen editor, "select" provides a cropping and zoom tool.
type (str): Type of value to be returned by component. "numpy" returns a numpy array with shape (width, height, 3), "pil" returns a PIL image object, "file" returns a temporary file object whose path can be retrieved by file_obj.name.
type (str): Type of value to be returned by component. "numpy" returns a numpy array with shape (width, height, 3) and values from 0 to 255, "pil" returns a PIL image object, "file" returns a temporary file object whose path can be retrieved by file_obj.name.
label (str): component name in interface.
'''
self.shape = shape
@ -257,6 +271,7 @@ class Image(InputComponent):
self.tool = tool
self.type = type
self.invert_colors = invert_colors
self.test_input = test_data.BASE64_IMAGE
super().__init__(label)
@classmethod
@ -293,6 +308,8 @@ class Image(InputComponent):
file_obj = tempfile.NamedTemporaryFile()
im.save(file_obj.name)
return file_obj
else:
raise ValueError("Unknown type: " + self.type + ". Please choose from: 'numpy', 'pil', 'file'.")
def process_example(self, example):
if os.path.exists(example):
@ -318,14 +335,15 @@ class Audio(InputComponent):
"""
def __init__(self, source="upload", type="numpy", label=None):
'''
"""
Parameters:
source (str): Source of audio. "upload" creates a box where user can drop an audio file, "microphone" creates a microphone input.
type (str): Type of value to be returned by component. "numpy" returns a 2-set tuple with an integer sample_rate and the data numpy.array of shape (samples, 2), "file" returns a temporary file object whose path can be retrieved by file_obj.name, "mfcc" returns the mfcc coefficients of the input audio.
label (str): component name in interface.
'''
"""
self.source = source
self.type = type
self.test_input = test_data.BASE64_AUDIO
super().__init__(label)
def get_template_context(self):
@ -367,6 +385,7 @@ class File(InputComponent):
label (str): component name in interface.
'''
self.type = type
self.test_input = None
super().__init__(label)
@classmethod
@ -391,7 +410,7 @@ class Dataframe(InputComponent):
"""
def __init__(self, headers=None, row_count=3, col_count=3, datatype="str", type="pandas", label=None):
'''
"""
Parameters:
headers (List[str]): Header names to dataframe.
row_count (int): Limit number of rows for input.
@ -399,14 +418,17 @@ class Dataframe(InputComponent):
datatype (Union[str, List[str]]): Datatype of values in sheet. Can be provided per column as a list of strings, or for the entire sheet as a single string. Valid datatypes are "str", "number", "bool", and "date".
type (str): Type of value to be returned by component. "pandas" for pandas dataframe, "numpy" for numpy array, or "array" for a Python array.
label (str): component name in interface.
'''
"""
self.headers = headers
self.datatype = datatype
self.row_count = row_count
self.col_count = len(headers) if headers else col_count
self.type = type
super().__init__(label)
sample_values = {"str": "abc", "number": 786, "bool": True, "date": "02/08/1993"}
column_dtypes = [datatype]*self.col_count if isinstance(datatype, str) else datatype
self.test_input = [[sample_values[c] for c in column_dtypes] for _ in range(row_count)]
super().__init__(label)
def get_template_context(self):
return {

24
build/lib/gradio/interface.py
View File

@ -193,19 +193,19 @@ class Interface:
return config
def process(self, raw_input):
def process(self, raw_input, predict_fn=None):
"""
:param raw_input: a list of raw inputs to process and apply the
prediction(s) on.
:param predict_fn: which function to process. If not provided, all of the model functions are used.
:return:
processed output: a list of processed outputs to return as the
prediction(s).
duration: a list of time deltas measuring inference time for each
prediction fn.
"""
processed_input = [input_interface.preprocess(
raw_input[i]) for i, input_interface in
enumerate(self.input_interfaces)]
processed_input = [input_interface.preprocess(raw_input[i])
for i, input_interface in enumerate(self.input_interfaces)]
predictions = []
durations = []
for predict_fn in self.predict:
@ -253,6 +253,22 @@ class Interface:
thread.keep_running = False
networking.url_ok(path_to_local_server)
def test_launch(self):
for predict_fn in self.predict:
print("Test launching: {}()...".format(predict_fn.__name__), end=' ')
raw_input = []
for input_interface in self.input_interfaces:
if input_interface.test_input is None: # If no test input is defined for that input interface
print("SKIPPED")
break
else: # If a test input is defined for each interface object
raw_input.append(input_interface.test_input)
else:
self.process(raw_input)
print("PASSED")
continue
def launch(self, inline=None, inbrowser=None, share=False, debug=False):
"""
Parameters

6
build/lib/gradio/static/css/style.css
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@ -7,17 +7,13 @@ body#lib {
button, input[type="submit"], input[type="reset"], input[type="text"], input[type="button"], select[type="submit"] {
border: none;
font: inherit;
cursor: pointer;
outline: inherit;
-webkit-appearance: none;
}
select {
font: inherit;
}
label, input[type=radio], input[type=checkbox], select, input[type=range] {
cursor: pointer;
}
button, input[type="submit"], input[type="reset"], input[type="button"], select[type="submit"] {
label, input[type=radio], input[type=checkbox], select, input[type=range], button, input[type="submit"], input[type="reset"], input[type="button"], select[type="submit"] {
cursor: pointer;
}

2
build/lib/gradio/test_data.py Normal file
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File diff suppressed because one or more lines are too long

2
gradio.egg-info/PKG-INFO
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@ -1,6 +1,6 @@
Metadata-Version: 1.0
Name: gradio
Version: 1.1.7
Version: 1.1.8.1
Summary: Python library for easily interacting with trained machine learning models
Home-page: https://github.com/gradio-app/gradio-UI
Author: Abubakar Abid

1
gradio.egg-info/SOURCES.txt
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@ -9,6 +9,7 @@ gradio/networking.py
gradio/outputs.py
gradio/processing_utils.py
gradio/strings.py
gradio/test_data.py
gradio/tunneling.py
gradio/utils.py
gradio.egg-info/PKG-INFO

2
setup.py
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@ -5,7 +5,7 @@ except ImportError:
setup(
name='gradio',
version='1.1.7',
version='1.1.8.1',
include_package_data=True,
description='Python library for easily interacting with trained machine learning models',
author='Abubakar Abid',