Metadata-Version: 2.1
Name: tf2show
Version: 0.0.5
Summary: tf2show prints tensorflow2's keras model pretty.
Home-page: https://github.com/springkim/tf2show
Author: Bomm Kim
Author-email: springnode@gmail.com
License: UNKNOWN
Description: # tf2show
        
        ## Install
        ```bash
        pip install tf2show
        ```
        
        ## Example
        ```python
        import tensorflow as tf
        from tf2show import tf2show
        
        model = tf.keras.applications.ResNet50()
        tf2show(model)	# show model structure
        tf2show(model,"model.xlsx")    # save model structure as excel file
        ```
        
        ## Description
        
        tf2show prints tensorflow2's keras model pretty.
        
        Below is the result of `summary` function provided in tensorflow2.
        
        It's not pretty. In addition, some output has been omitted.
        
        ```
        Model: "mobilenet_1.00_256"
        _________________________________________________________________
        Layer (type)                 Output Shape              Param #   
        =================================================================
        input_1 (InputLayer)         [(None, 256, 256, 3)]     0         
        _________________________________________________________________
        conv1_pad (ZeroPadding2D)    (None, 257, 257, 3)       0         
        _________________________________________________________________
        conv1 (Conv2D)               (None, 128, 128, 32)      864       
        _________________________________________________________________
        conv1_bn (BatchNormalization (None, 128, 128, 32)      128       
        _________________________________________________________________
        conv1_relu (ReLU)            (None, 128, 128, 32)      0         
        _________________________________________________________________
        conv_dw_1 (DepthwiseConv2D)  (None, 128, 128, 32)      288       
        _________________________________________________________________
        .
        .
        .
        _________________________________________________________________
        reshape_2 (Reshape)          (None, 1000)              0         
        _________________________________________________________________
        predictions (Activation)     (None, 1000)              0         
        =================================================================
        Total params: 4,253,864
        Trainable params: 4,231,976
        Non-trainable params: 21,888
        _________________________________________________________________
        ```
        
        Below is the output using tf2show.
        
        It's pretty. All names are printed.
        
        ```
        ----------------------------------------------------------------------------------------------------
        | LAYER                  | NAME                     | C    | H   | W    | INPUTS                   |
        ----------------------------------------------------------------------------------------------------
        | InputLayer             | input_1                  | 3    | 256 | 256  | input_1:0                |
        | ZeroPadding2D          | conv1_pad                | 3    | 257 | 257  | input_1:0                |
        | Conv2D                 | conv1                    | 32   | 128 | 128  | conv1_pad                |
        | BatchNormalization     | conv1_bn                 | 32   | 128 | 128  | conv1                    |
        | ReLU                   | conv1_relu               | 32   | 128 | 128  | conv1_bn                 |
        | DepthwiseConv2D        | conv_dw_1                | 32   | 128 | 128  | conv1_relu               |
        | BatchNormalization     | conv_dw_1_bn             | 32   | 128 | 128  | conv_dw_1                |
        | ReLU                   | conv_dw_1_relu           | 32   | 128 | 128  | conv_dw_1_bn             |
        | Conv2D                 | conv_pw_1                | 64   | 128 | 128  | conv_dw_1_relu           |
        | BatchNormalization     | conv_pw_1_bn             | 64   | 128 | 128  | conv_pw_1                |
        | ReLU                   | conv_pw_1_relu           | 64   | 128 | 128  | conv_pw_1_bn             |
        | ZeroPadding2D          | conv_pad_2               | 64   | 129 | 129  | conv_pw_1_relu           |
        | DepthwiseConv2D        | conv_dw_2                | 64   | 64  | 64   | conv_pad_2               |
        .
        .
        .
        | Reshape                | reshape_2                |      |     | 1000 | conv_preds               |
        | Activation             | predictions              |      |     | 1000 | reshape_2                |
        ----------------------------------------------------------------------------------------------------
        ```
        
        
        It also supports saving to Excel.
        
        This function can be useful when analyzing models.
        
        ### Get a quick view of the hardware resources required for deep learning.
        ```python
        import tf2show
        tf2show.hw4show()
        
        ```
        
        #### `Linux`
        ```
        CPU: Intel(R) Xeon(R) CPU @ 2.00GHz 2C/4T
        RAM: 15.64 GB
        GPU: Tesla P100-PCIE-16GB, 15.9 GB
        ```
        #### `Windows`
        ```
        CPU: Intel(R) Core(TM) i7-6950X CPU @ 3.00GHz 10C/20T
        RAM: 32.00 GB
        GPU: GeForce RTX 2080 Ti, 11.0 GB
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
