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interface and launch refactoring, documentation

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This commit is contained in:
aliabd 2020-08-03 11:43:58 -07:00
parent 82d622028c
commit e5f7efdbe1
3 changed files with 105 additions and 53 deletions
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110
gradio/interface.py
View File

@ -8,7 +8,7 @@ import webbrowser
import gradio.inputs
import gradio.outputs
from gradio import networking, strings
from gradio import networking, strings, utils
from distutils.version import StrictVersion
import pkg_resources
import requests
@ -21,6 +21,7 @@ import weakref
import analytics
import os
PKG_VERSION_URL = "https://gradio.app/api/pkg-version"
analytics.write_key = "uxIFddIEuuUcFLf9VgH2teTEtPlWdkNy"
analytics_url = 'https://api.gradio.app/'
@ -29,13 +30,22 @@ try:
except requests.ConnectionError:
ip_address = "No internet connection"
class Interface:
"""
Interfaces are created with Gradio using the `gradio.Interface()` function.
"""
instances = weakref.WeakSet()
def __init__(self, fn, inputs, outputs, saliency=None, verbose=False, examples=None,
@classmethod
def get_instances(cls):
"""
:return: list of all current instances.
"""
return list(
Interface.instances)
def __init__(self, fn, inputs, outputs, verbose=False, examples=None,
live=False, show_input=True, show_output=True,
capture_session=False, title=None, description=None,
thumbnail=None, server_port=None, server_name=networking.LOCALHOST_NAME,
@ -46,11 +56,23 @@ class Interface:
fn (Callable): the function to wrap an interface around.
inputs (Union[str, List[Union[str, AbstractInput]]]): a single Gradio input component, or list of Gradio input components. Components can either be passed as instantiated objects, or referred to by their string shortcuts. The number of input components should match the number of parameters in fn.
outputs (Union[str, List[Union[str, AbstractOutput]]]): a single Gradio output component, or list of Gradio output components. Components can either be passed as instantiated objects, or referred to by their string shortcuts. The number of output components should match the number of values returned by fn.
verbose (bool): whether to print detailed information during launch.
examples (List[List[Any]]): sample inputs for the function; if provided, appears below the UI components and can be used to populate the interface. Should be nested list, in which the outer list consists of samples and each inner list consists of an input corresponding to each input component.
live (bool): whether the interface should automatically reload on change.
show_input (bool): if False, removes the input from the interface
and underlays it in the output.
show_output (bool): if False, removes the output from the interface
and overlays it in the input.
capture_session (bool): if True, captures the default graph and session (needed for Tensorflow 1.x)
title (str): a title for the interface; if provided, appears above the input and output components.
description (str): a description for the interface; if provided, appears above the input and output components.
examples (List[List[Any]]): sample inputs for the function; if provided, appears below the UI components and can be used to populate the interface. Should be nested list, in which the outer list consists of samples and each inner list consists of an input corresponding to each input component.
thumbnail (str): path to image or src to use as display picture for
models listed in gradio.app/hub
allow_screenshot (bool): if False, users will not see a button to
take a screenshot of the interface.
allow_flagging (bool): if False, users will not see a button to flag an
input and output.
flagging_dir (str): what to name the dir where flagged data is stored.
"""
def get_input_instance(iface):
if isinstance(iface, str):
@ -81,11 +103,11 @@ class Interface:
self.output_interfaces = [get_output_instance(outputs)]
if not isinstance(fn, list):
fn = [fn]
self.output_interfaces *= len(fn)
self.predict = fn
self.verbose = verbose
self.status = "OFF"
self.saliency = saliency
self.live = live
self.show_input = show_input
self.show_output = show_output
@ -107,7 +129,6 @@ class Interface:
data = {'fn': fn,
'inputs': inputs,
'outputs': outputs,
'saliency': saliency,
'live': live,
'capture_session': capture_session,
'ip_address': ip_address
@ -118,7 +139,9 @@ class Interface:
import tensorflow as tf
self.session = tf.get_default_graph(), \
tf.keras.backend.get_session()
except (ImportError, AttributeError): # If they are using TF >= 2.0 or don't have TF, just ignore this.
except (ImportError, AttributeError):
# If they are using TF >= 2.0 or don't have TF,
# just ignore this.
pass
if self.allow_flagging:
@ -172,6 +195,15 @@ class Interface:
return config
def process(self, raw_input):
"""
:param raw_input: a list of raw inputs to process and apply the
prediction(s) on.
: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)]
@ -216,8 +248,18 @@ class Interface:
def launch(self, inline=None, inbrowser=None, share=False, debug=False):
"""
Parameters
inline (bool): whether to display in the interface inline on python
notebooks.
inbrowser (bool): whether to automatically launch the interface in a
new tab on the default browser.
share (bool): whether to create a publicly shareable link from
your computer for the interface.
debug (bool): if True, and the interface was launched from Google
Colab, prints the errors in the cell output.
:returns
httpd (str): HTTPServer object
path_to_local_server (str): Locally accessible link
share_url (str): Publicly accessible link (if share=True)
"""
output_directory = tempfile.mkdtemp()
@ -231,20 +273,6 @@ class Interface:
self.status = "RUNNING"
self.simple_server = httpd
is_colab = False
try: # Check if running interactively using ipython.
from_ipynb = get_ipython()
if "google.colab" in str(from_ipynb):
is_colab = True
except NameError:
data = {'error': 'NameError in launch method'}
try:
requests.post(analytics_url + 'gradio-error-analytics/',
data=data)
except requests.ConnectionError:
pass # do not push analytics if no network
pass
try:
current_pkg_version = pkg_resources.require("gradio")[0].version
latest_pkg_version = requests.get(url=PKG_VERSION_URL).json()["version"]
@ -257,6 +285,7 @@ class Interface:
except: # TODO(abidlabs): don't catch all exceptions
pass
is_colab = utils.colab_check()
if not is_colab:
print(strings.en["RUNNING_LOCALLY"].format(path_to_local_server))
else:
@ -271,19 +300,13 @@ class Interface:
share_url = networking.setup_tunnel(server_port)
print("Running on External URL:", share_url)
except RuntimeError:
data = {'error': 'RuntimeError in launch method'}
try:
requests.post(analytics_url + 'gradio-error-analytics/',
data=data)
except requests.ConnectionError:
pass # do not push analytics if no network
utils.error_analytics("RuntimeError")
share_url = None
if self.verbose:
print(strings.en["NGROK_NO_INTERNET"])
else:
if (
is_colab
): # For a colab notebook, create a public link even if share is False.
if is_colab: # For a colab notebook, create a public link even if
# share is False.
share_url = networking.setup_tunnel(server_port)
print("Running on External URL:", share_url)
if self.verbose:
@ -294,29 +317,22 @@ class Interface:
share_url = None
if inline is None:
try: # Check if running interactively using ipython.
get_ipython()
inline = True
if inbrowser is None:
inbrowser = False
except NameError:
inline = False
if inbrowser is None:
inbrowser = True
inline = utils.ipython_check()
if inbrowser is None:
# if interface won't appear inline, open it in new tab,
# otherwise keep it inline
inbrowser = not inline
else:
if inbrowser is None:
inbrowser = False
if inbrowser and not is_colab:
webbrowser.open(
path_to_local_server
) # Open a browser tab with the interface.
webbrowser.open(path_to_local_server) # Open a browser tab
# with the interface.
if inline:
from IPython.display import IFrame, display
if (
is_colab
): # Embed the remote interface page if on google colab;
if (is_colab):
# Embed the remote interface page if on google colab;
# otherwise, embed the local page.
print("Interface loading below...")
while not networking.url_ok(share_url):
@ -359,10 +375,6 @@ class Interface:
pass # do not push analytics if no network
return httpd, path_to_local_server, share_url
@classmethod
def get_instances(cls):
return list(Interface.instances) # Returns list of all current instances.
def reset_all():
for io in Interface.get_instances():

4
gradio/networking.py
View File

@ -169,10 +169,6 @@ def serve_files_in_background(interface, port, directory_to_serve=None, server_n
prediction, durations = interface.process(raw_input)
output = {"data": prediction, "durations": durations}
if interface.saliency is not None:
saliency = interface.saliency(raw_input, prediction)
output['saliency'] = saliency.tolist()
self.wfile.write(json.dumps(output).encode())
analytics_thread = threading.Thread(

44
gradio/utils.py Normal file
View File

@ -0,0 +1,44 @@
import requests
from IPython import get_ipython
analytics_url = 'https://api.gradio.app/'
def error_analytics(type):
"""
Send error analytics if there is network
:param type: RuntimeError or NameError
"""
data = {'error': '{} in launch method'.format(type)}
try:
requests.post(analytics_url + 'gradio-error-analytics/',
data=data)
except requests.ConnectionError:
pass # do not push analytics if no network
def colab_check():
"""
Check if interface is launching from Google Colab
:return is_colab (bool): True or False
"""
is_colab = False
try: # Check if running interactively using ipython.
from_ipynb = get_ipython()
if "google.colab" in str(from_ipynb):
is_colab = True
except NameError:
error_analytics("NameError", analytics_url)
return is_colab
def ipython_check():
"""
Check if interface is launching from iPython (not colab)
:return is_ipython (bool): True or False
"""
try: # Check if running interactively using ipython.
get_ipython()
is_ipython = True
except NameError:
is_ipython = False
return is_ipython