Metadata-Version: 2.1
Name: tflite2tensorflow
Version: 0.1.2
Summary: Generate saved_model and .pb from .tflite.
Home-page: https://github.com/PINTO0309/tflite2tensorflow
Author: Katsuya Hyodo
Author-email: rmsdh122@yahoo.co.jp
License: MIT License
Description: # tflite2tensorflow
        
        <p align="center">
          <img src="https://user-images.githubusercontent.com/33194443/105187518-38ac0c00-5b76-11eb-869b-b518df146924.png" />
        </p>
        
        【WIP】 Generate saved_model, tfjs, tf-trt, EdgeTPU, CoreML, quantized tflite and .pb from .tflite.
        
        [![PyPI - Downloads](https://img.shields.io/pypi/dm/tflite2tensorflow?color=2BAF2B&label=Downloads%EF%BC%8FInstalled)](https://pypistats.org/packages/tflite2tensorflow) ![GitHub](https://img.shields.io/github/license/PINTO0309/tflite2tensorflow?color=2BAF2B) [![PyPI](https://img.shields.io/pypi/v/tflite2tensorflow?color=2BAF2B)](https://pypi.org/project/tflite2tensorflow/)
        
        ## 1. Supported Layers
        
        |No.|TFLite Layer|TF Layer|Remarks|
        |:--:|:--|:--|:--|
        |1|CONV_2D|tf.nn.conv2d||
        |2|DEPTHWISE_CONV_2D|tf.nn.depthwise_conv2d||
        |3|MAX_POOL_2D|tf.nn.max_pool||
        |4|PAD|tf.pad||
        |5|MIRROR_PAD|tf.raw_ops.MirrorPad||
        |6|RELU|tf.nn.relu||
        |7|PRELU|tf.keras.layers.PReLU||
        |8|RELU6|tf.nn.relu6||
        |9|RESHAPE|tf.reshape||
        |10|ADD|tf.add||
        |11|SUB|tf.math.subtract||
        |12|CONCATENATION|tf.concat||
        |13|LOGISTIC|tf.math.sigmoid||
        |14|TRANSPOSE_CONV|tf.nn.conv2d_transpose||
        |15|MUL|tf.multiply||
        |16|HARD_SWISH|x\*tf.nn.relu6(x+3)\*0.16666667 Or x\*tf.nn.relu6(x+3)\*0.16666666||
        |17|AVERAGE_POOL_2D|tf.keras.layers.AveragePooling2D||
        |18|FULLY_CONNECTED|tf.keras.layers.Dense||
        |19|RESIZE_BILINEAR|tf.image.resize Or tf.image.resize_bilinear||
        |20|RESIZE_NEAREST_NEIGHBOR|tf.image.resize Or tf.image.resize_nearest_neighbor||
        |21|MEAN|tf.math.reduce_mean||
        |22|SQUARED_DIFFERENCE|tf.math.squared_difference||
        |23|RSQRT|tf.math.rsqrt||
        |24|DEQUANTIZE|(const)||
        |25|FLOOR|tf.math.floor||
        |26|TANH|tf.math.tanh||
        |27|DIV|tf.math.divide||
        |28|FLOOR_DIV|tf.math.floordiv||
        |29|SUM|tf.math.reduce_sum||
        |30|POW|tf.math.pow||
        |31|SPLIT|tf.split||
        
        ## 2. Environment
        - Python3.6+
        - TensorFlow v2.4.0+ or tf-nightly
        
        ## 3. Setup
        To install using the Python Package Index (PyPI), use the following command.
        ```
        $ pip3 install tflite2tensorflow --upgrade
        ```
        To install with the latest source code of the main branch, use the following command.
        ```
        $ pip3 install git+https://github.com/PINTO0309/tflite2tensorflow --upgrade
        ```
        ## 4. Usage / Execution sample
        ### 4-1. Step 1 : Generating saved_model and FreezeGraph (.pb)
        ```
        $ tflite2tensorflow \
          --model_path magenta_arbitrary-image-stylization-v1-256_fp16_prediction_1.tflite \
          --flatc_path ./flatc \
          --schema_path schema.fbs \
          --output_pb True
        ```
        or
        ```
        $ tflite2tensorflow \
          --model_path magenta_arbitrary-image-stylization-v1-256_fp16_prediction_1.tflite \
          --flatc_path ./flatc \
          --schema_path schema.fbs \
          --output_pb True \
          --optimizing_hardswish_for_edgetpu True
        ```
        ### 4-2. Step 2 : Generation of quantized tflite, TFJS, TF-TRT, EdgeTPU, and CoreML
        ```
        $ tflite2tensorflow \
          --model_path magenta_arbitrary-image-stylization-v1-256_fp16_prediction_1.tflite \
          --flatc_path ./flatc \
          --schema_path schema.fbs \
          --output_no_quant_float32_tflite True \
          --output_weight_quant_tflite True \
          --output_float16_quant_tflite True \
          --output_integer_quant_tflite True \
          --string_formulas_for_normalization 'data / 255.0' \
          --output_tfjs True \
          --output_coreml True \
          --output_tftrt True
        ```
        or
        ```
        $ tflite2tensorflow \
          --model_path magenta_arbitrary-image-stylization-v1-256_fp16_prediction_1.tflite \
          --flatc_path ./flatc \
          --schema_path schema.fbs \
          --output_no_quant_float32_tflite True \
          --output_weight_quant_tflite True \
          --output_float16_quant_tflite True \
          --output_integer_quant_tflite True \
          --output_edgetpu True \
          --string_formulas_for_normalization 'data / 255.0' \
          --output_tfjs True \
          --output_coreml True \
          --output_tftrt True
        ```
        
Platform: linux
Platform: unix
Requires-Python: >3.6
Description-Content-Type: text/markdown
