remove keras example from python documentation (#6574)

docs/python/examples/plot_dl_keras.py

@@ -1,94 +0,0 @@
-# Copyright (c) Microsoft Corporation. All rights reserved.
-# Licensed under the MIT License.
-
-"""
-
-.. _l-example-backend-api-tensorflow:
-
-ONNX Runtime for Keras
-======================
-
-The following demonstrates how to compute the predictions
-of a pretrained deep learning model obtained from 
-`keras <https://keras.io/>`_
-with *onnxruntime*. The conversion requires
-`keras <https://keras.io/>`_,
-`tensorflow <https://www.tensorflow.org/>`_,
-`keras-onnx <https://github.com/onnx/keras-onnx/>`_,
-`onnxmltools <https://pypi.org/project/onnxmltools/>`_
-but then only *onnxruntime* is required
-to compute the predictions.
-"""
-import os
-if not os.path.exists('dense121.onnx'):
-    from keras.applications.densenet import DenseNet121
-    model = DenseNet121(include_top=True, weights='imagenet')
-
-    from keras2onnx import convert_keras
-    onx = convert_keras(model, 'dense121.onnx')
-    with open("dense121.onnx", "wb") as f:
-        f.write(onx.SerializeToString())
-
-##################################
-# Let's load an image (source: wikipedia).
-
-from keras.preprocessing.image import array_to_img, img_to_array, load_img
-img = load_img('Sannosawa1.jpg')
-ximg = img_to_array(img)
-
-import matplotlib.pyplot as plt
-plt.imshow(ximg / 255)
-plt.axis('off')
-
-#############################################
-# Let's load the model with onnxruntime.
-import onnxruntime as rt
-from onnxruntime.capi.onnxruntime_pybind11_state import InvalidGraph
-
-try:
-    sess = rt.InferenceSession('dense121.onnx')
-    ok = True
-except (InvalidGraph, TypeError, RuntimeError) as e:
-    # Probably a mismatch between onnxruntime and onnx version.
-    print(e)
-    ok = False
-
-if ok:
-    print("The model expects input shape:", sess.get_inputs()[0].shape)
-    print("image shape:", ximg.shape)
-
-#######################################
-# Let's resize the image.
-
-if ok:
-    from skimage.transform import resize
-    import numpy
-
-    ximg224 = resize(ximg / 255, (224, 224, 3), anti_aliasing=True)
-    ximg = ximg224[numpy.newaxis, :, :, :]
-    ximg = ximg.astype(numpy.float32)
-
-    print("new shape:", ximg.shape)
-
-##################################
-# Let's compute the output.
-
-if ok:
-    input_name = sess.get_inputs()[0].name
-    res = sess.run(None, {input_name: ximg})
-    prob = res[0]
-    print(prob.ravel()[:10])  # Too big to be displayed.
-
-
-##################################
-# Let's get more comprehensive results.
-
-if ok:
-    from keras.applications.densenet import decode_predictions
-    decoded = decode_predictions(prob)
-
-    import pandas
-    df = pandas.DataFrame(decoded[0], columns=["class_id", "name", "P"])
-    print(df)
-
-

docs/python/requirements.txt

@@ -1,5 +1,3 @@
-keras
-keras-onnx
 sphinx
 sphinx-gallery
 pyquickhelper

tools/doc/rename_folders.py

@@ -23,6 +23,8 @@ def rename_folder(root):
         renamed.append((r, name, into))
         full_src = os.path.join(r, name)
         full_into = os.path.join(r, into)
+        if os.path.exists(full_into):
+            raise RuntimeError("%r already exists, previous documentation should be removed.")
         print("rename %r" % full_src)
         os.rename(full_src, full_into)