Tutorial enhancement to keep it clean on docs.tvm.ai #1450
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@masahi @siju-samuel @PariksheetPinjari909 welcome to review pls. |
masahi
reviewed
Jul 19, 2018
tutorials/nnvm/from_tensorflow.py
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| # .. note:: | ||
| # | ||
| # tensorflow frontend import doesn't support preprocessing ops like JpegDecode | ||
| # JpegDecode is a bypass (copy source) here. |
masahi
reviewed
Jul 19, 2018
tutorials/nnvm/from_tensorflow.py
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| # --------------------------------------------------- | ||
| # Inference on tensorflow | ||
| # ----------------------- | ||
| # Now lets run the same on tensorflow |
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run the corresponding model on tensorflow
siju-samuel
reviewed
Jul 19, 2018
tutorials/nnvm/from_tensorflow.py
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| For us to begin with, tensorflow module is required to be installed. | ||
| For us to begin with, tensorflow python module is required to be installed. | ||
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| A quick solution is to install tensorlfow from |
tutorials/nnvm/from_tensorflow.py
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| # -------------------------------------- | ||
| # Import model | ||
| # ------------ | ||
| # Creates tensorflow graph definition from protobuf file. | ||
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| with tf.gfile.FastGFile(os.path.join( | ||
| "./", model_name), 'rb') as f: |
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with tf.gfile.FastGFile(os.path.join("./", model_name), 'rb') as f:
keep as single line
| # JpegDecode is a bypass (copy source) here. | ||
| # Hence we supply decoded frame to TVM instead. | ||
| # | ||
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| from PIL import Image | ||
| image = Image.open(img_name).resize((299, 299)) | ||
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transform_image
suggest to use _transform_image for private functions..
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@masahi & @siju-samuel thanks for the review. Handled the review comments now. |
PariksheetPinjari909
approved these changes
Jul 19, 2018
masahi
approved these changes
Jul 19, 2018
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Thanks, @srkreddy1238 @masahi @PariksheetPinjari909 @siju-samuel , this is now merged! |
tqchen
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sergei-mironov
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