Comments (1)
0buo
commented on June 16, 2024
I print out the ops in the frozen graph and only see the generator model: (ignore all the 'prefix/' in names)
name: prefix/z | type: Placeholder | outputs: [<tf.Tensor 'prefix/z:0' shape=(?, 512) dtype=float32>]
name: prefix/generator/g_h0_lin/Matrix | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_h0_lin/Matrix:0' shape=(512, 131072) dtype=float32>]
name: prefix/generator/g_h0_lin/Matrix/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_h0_lin/Matrix/read:0' shape=(512, 131072) dtype=float32>]
name: prefix/generator/g_h0_lin/bias | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_h0_lin/bias:0' shape=(131072,) dtype=float32>]
name: prefix/generator/g_h0_lin/bias/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_h0_lin/bias/read:0' shape=(131072,) dtype=float32>]
name: prefix/generator/g_bn0/beta | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn0/beta:0' shape=(512,) dtype=float32>]
name: prefix/generator/g_bn0/beta/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn0/beta/read:0' shape=(512,) dtype=float32>]
name: prefix/generator/g_bn0/gamma | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn0/gamma:0' shape=(512,) dtype=float32>]
name: prefix/generator/g_bn0/gamma/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn0/gamma/read:0' shape=(512,) dtype=float32>]
name: prefix/generator/g_bn0/moving_mean | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn0/moving_mean:0' shape=(512,) dtype=float32>]
name: prefix/generator/g_bn0/moving_mean/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn0/moving_mean/read:0' shape=(512,) dtype=float32>]
name: prefix/generator/g_bn0/moving_variance | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn0/moving_variance:0' shape=(512,) dtype=float32>]
name: prefix/generator/g_bn0/moving_variance/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn0/moving_variance/read:0' shape=(512,) dtype=float32>]
name: prefix/generator/g_h1/w | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_h1/w:0' shape=(5, 5, 256, 512) dtype=float32>]
name: prefix/generator/g_h1/w/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_h1/w/read:0' shape=(5, 5, 256, 512) dtype=float32>]
name: prefix/generator/g_h1/biases | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_h1/biases:0' shape=(256,) dtype=float32>]
name: prefix/generator/g_h1/biases/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_h1/biases/read:0' shape=(256,) dtype=float32>]
name: prefix/generator/g_bn1/beta | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn1/beta:0' shape=(256,) dtype=float32>]
name: prefix/generator/g_bn1/beta/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn1/beta/read:0' shape=(256,) dtype=float32>]
name: prefix/generator/g_bn1/gamma | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn1/gamma:0' shape=(256,) dtype=float32>]
name: prefix/generator/g_bn1/gamma/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn1/gamma/read:0' shape=(256,) dtype=float32>]
name: prefix/generator/g_bn1/moving_mean | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn1/moving_mean:0' shape=(256,) dtype=float32>]
name: prefix/generator/g_bn1/moving_mean/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn1/moving_mean/read:0' shape=(256,) dtype=float32>]
name: prefix/generator/g_bn1/moving_variance | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn1/moving_variance:0' shape=(256,) dtype=float32>]
name: prefix/generator/g_bn1/moving_variance/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn1/moving_variance/read:0' shape=(256,) dtype=float32>]
name: prefix/generator/g_h2/w | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_h2/w:0' shape=(5, 5, 128, 256) dtype=float32>]
name: prefix/generator/g_h2/w/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_h2/w/read:0' shape=(5, 5, 128, 256) dtype=float32>]
name: prefix/generator/g_h2/biases | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_h2/biases:0' shape=(128,) dtype=float32>]
name: prefix/generator/g_h2/biases/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_h2/biases/read:0' shape=(128,) dtype=float32>]
name: prefix/generator/g_bn2/beta | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn2/beta:0' shape=(128,) dtype=float32>]
name: prefix/generator/g_bn2/beta/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn2/beta/read:0' shape=(128,) dtype=float32>]
name: prefix/generator/g_bn2/gamma | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn2/gamma:0' shape=(128,) dtype=float32>]
name: prefix/generator/g_bn2/gamma/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn2/gamma/read:0' shape=(128,) dtype=float32>]
name: prefix/generator/g_bn2/moving_mean | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn2/moving_mean:0' shape=(128,) dtype=float32>]
name: prefix/generator/g_bn2/moving_mean/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn2/moving_mean/read:0' shape=(128,) dtype=float32>]
name: prefix/generator/g_bn2/moving_variance | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn2/moving_variance:0' shape=(128,) dtype=float32>]
name: prefix/generator/g_bn2/moving_variance/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn2/moving_variance/read:0' shape=(128,) dtype=float32>]
name: prefix/generator/g_h3/w | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_h3/w:0' shape=(5, 5, 64, 128) dtype=float32>]
name: prefix/generator/g_h3/w/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_h3/w/read:0' shape=(5, 5, 64, 128) dtype=float32>]
name: prefix/generator/g_h3/biases | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_h3/biases:0' shape=(64,) dtype=float32>]
name: prefix/generator/g_h3/biases/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_h3/biases/read:0' shape=(64,) dtype=float32>]
name: prefix/generator/g_bn3/beta | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn3/beta:0' shape=(64,) dtype=float32>]
name: prefix/generator/g_bn3/beta/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn3/beta/read:0' shape=(64,) dtype=float32>]
name: prefix/generator/g_bn3/gamma | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn3/gamma:0' shape=(64,) dtype=float32>]
name: prefix/generator/g_bn3/gamma/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn3/gamma/read:0' shape=(64,) dtype=float32>]
name: prefix/generator/g_bn3/moving_mean | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn3/moving_mean:0' shape=(64,) dtype=float32>]
name: prefix/generator/g_bn3/moving_mean/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn3/moving_mean/read:0' shape=(64,) dtype=float32>]
name: prefix/generator/g_bn3/moving_variance | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_bn3/moving_variance:0' shape=(64,) dtype=float32>]
name: prefix/generator/g_bn3/moving_variance/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_bn3/moving_variance/read:0' shape=(64,) dtype=float32>]
name: prefix/generator/g_h4/w | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_h4/w:0' shape=(5, 5, 3, 64) dtype=float32>]
name: prefix/generator/g_h4/w/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_h4/w/read:0' shape=(5, 5, 3, 64) dtype=float32>]
name: prefix/generator/g_h4/biases | type: Const | outputs: [<tf.Tensor 'prefix/generator/g_h4/biases:0' shape=(3,) dtype=float32>]
name: prefix/generator/g_h4/biases/read | type: Identity | outputs: [<tf.Tensor 'prefix/generator/g_h4/biases/read:0' shape=(3,) dtype=float32>]
name: prefix/generator_1/g_h0_lin/MatMul | type: MatMul | outputs: [<tf.Tensor 'prefix/generator_1/g_h0_lin/MatMul:0' shape=(?, 131072) dtype=float32>]
name: prefix/generator_1/g_h0_lin/add | type: AddV2 | outputs: [<tf.Tensor 'prefix/generator_1/g_h0_lin/add:0' shape=(?, 131072) dtype=float32>]
name: prefix/generator_1/Reshape/shape | type: Const | outputs: [<tf.Tensor 'prefix/generator_1/Reshape/shape:0' shape=(4,) dtype=int32>]
name: prefix/generator_1/Reshape | type: Reshape | outputs: [<tf.Tensor 'prefix/generator_1/Reshape:0' shape=(?, 16, 16, 512) dtype=float32>]
name: prefix/generator_1/g_bn0/FusedBatchNormV3 | type: FusedBatchNormV3 | outputs: [<tf.Tensor 'prefix/generator_1/g_bn0/FusedBatchNormV3:0' shape=(?, 16, 16, 512) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn0/FusedBatchNormV3:1' shape=(512,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn0/FusedBatchNormV3:2' shape=(512,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn0/FusedBatchNormV3:3' shape=(512,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn0/FusedBatchNormV3:4' shape=(512,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn0/FusedBatchNormV3:5' shape=<unknown> dtype=float32>]
name: prefix/generator_1/Relu | type: Relu | outputs: [<tf.Tensor 'prefix/generator_1/Relu:0' shape=(?, 16, 16, 512) dtype=float32>]
name: prefix/generator_1/g_h1/conv2d_transpose/input_sizes | type: Const | outputs: [<tf.Tensor 'prefix/generator_1/g_h1/conv2d_transpose/input_sizes:0' shape=(4,) dtype=int32>]
name: prefix/generator_1/g_h1/conv2d_transpose | type: Conv2DBackpropInput | outputs: [<tf.Tensor 'prefix/generator_1/g_h1/conv2d_transpose:0' shape=(1, 32, 32, 256) dtype=float32>]
name: prefix/generator_1/g_h1/BiasAdd | type: BiasAdd | outputs: [<tf.Tensor 'prefix/generator_1/g_h1/BiasAdd:0' shape=(1, 32, 32, 256) dtype=float32>]
name: prefix/generator_1/g_h1/Reshape/shape | type: Const | outputs: [<tf.Tensor 'prefix/generator_1/g_h1/Reshape/shape:0' shape=(4,) dtype=int32>]
name: prefix/generator_1/g_h1/Reshape | type: Reshape | outputs: [<tf.Tensor 'prefix/generator_1/g_h1/Reshape:0' shape=(1, 32, 32, 256) dtype=float32>]
name: prefix/generator_1/g_bn1/FusedBatchNormV3 | type: FusedBatchNormV3 | outputs: [<tf.Tensor 'prefix/generator_1/g_bn1/FusedBatchNormV3:0' shape=(1, 32, 32, 256) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn1/FusedBatchNormV3:1' shape=(256,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn1/FusedBatchNormV3:2' shape=(256,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn1/FusedBatchNormV3:3' shape=(256,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn1/FusedBatchNormV3:4' shape=(256,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn1/FusedBatchNormV3:5' shape=<unknown> dtype=float32>]
name: prefix/generator_1/Relu_1 | type: Relu | outputs: [<tf.Tensor 'prefix/generator_1/Relu_1:0' shape=(1, 32, 32, 256) dtype=float32>]
name: prefix/generator_1/g_h2/conv2d_transpose/input_sizes | type: Const | outputs: [<tf.Tensor 'prefix/generator_1/g_h2/conv2d_transpose/input_sizes:0' shape=(4,) dtype=int32>]
name: prefix/generator_1/g_h2/conv2d_transpose | type: Conv2DBackpropInput | outputs: [<tf.Tensor 'prefix/generator_1/g_h2/conv2d_transpose:0' shape=(1, 64, 64, 128) dtype=float32>]
name: prefix/generator_1/g_h2/BiasAdd | type: BiasAdd | outputs: [<tf.Tensor 'prefix/generator_1/g_h2/BiasAdd:0' shape=(1, 64, 64, 128) dtype=float32>]
name: prefix/generator_1/g_h2/Reshape/shape | type: Const | outputs: [<tf.Tensor 'prefix/generator_1/g_h2/Reshape/shape:0' shape=(4,) dtype=int32>]
name: prefix/generator_1/g_h2/Reshape | type: Reshape | outputs: [<tf.Tensor 'prefix/generator_1/g_h2/Reshape:0' shape=(1, 64, 64, 128) dtype=float32>]
name: prefix/generator_1/g_bn2/FusedBatchNormV3 | type: FusedBatchNormV3 | outputs: [<tf.Tensor 'prefix/generator_1/g_bn2/FusedBatchNormV3:0' shape=(1, 64, 64, 128) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn2/FusedBatchNormV3:1' shape=(128,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn2/FusedBatchNormV3:2' shape=(128,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn2/FusedBatchNormV3:3' shape=(128,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn2/FusedBatchNormV3:4' shape=(128,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn2/FusedBatchNormV3:5' shape=<unknown> dtype=float32>]
name: prefix/generator_1/Relu_2 | type: Relu | outputs: [<tf.Tensor 'prefix/generator_1/Relu_2:0' shape=(1, 64, 64, 128) dtype=float32>]
name: prefix/generator_1/g_h3/conv2d_transpose/input_sizes | type: Const | outputs: [<tf.Tensor 'prefix/generator_1/g_h3/conv2d_transpose/input_sizes:0' shape=(4,) dtype=int32>]
name: prefix/generator_1/g_h3/conv2d_transpose | type: Conv2DBackpropInput | outputs: [<tf.Tensor 'prefix/generator_1/g_h3/conv2d_transpose:0' shape=(1, 128, 128, 64) dtype=float32>]
name: prefix/generator_1/g_h3/BiasAdd | type: BiasAdd | outputs: [<tf.Tensor 'prefix/generator_1/g_h3/BiasAdd:0' shape=(1, 128, 128, 64) dtype=float32>]
name: prefix/generator_1/g_h3/Reshape/shape | type: Const | outputs: [<tf.Tensor 'prefix/generator_1/g_h3/Reshape/shape:0' shape=(4,) dtype=int32>]
name: prefix/generator_1/g_h3/Reshape | type: Reshape | outputs: [<tf.Tensor 'prefix/generator_1/g_h3/Reshape:0' shape=(1, 128, 128, 64) dtype=float32>]
name: prefix/generator_1/g_bn3/FusedBatchNormV3 | type: FusedBatchNormV3 | outputs: [<tf.Tensor 'prefix/generator_1/g_bn3/FusedBatchNormV3:0' shape=(1, 128, 128, 64) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn3/FusedBatchNormV3:1' shape=(64,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn3/FusedBatchNormV3:2' shape=(64,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn3/FusedBatchNormV3:3' shape=(64,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn3/FusedBatchNormV3:4' shape=(64,) dtype=float32>, <tf.Tensor 'prefix/generator_1/g_bn3/FusedBatchNormV3:5' shape=<unknown> dtype=float32>]
name: prefix/generator_1/Relu_3 | type: Relu | outputs: [<tf.Tensor 'prefix/generator_1/Relu_3:0' shape=(1, 128, 128, 64) dtype=float32>]
name: prefix/generator_1/g_h4/conv2d_transpose/input_sizes | type: Const | outputs: [<tf.Tensor 'prefix/generator_1/g_h4/conv2d_transpose/input_sizes:0' shape=(4,) dtype=int32>]
name: prefix/generator_1/g_h4/conv2d_transpose | type: Conv2DBackpropInput | outputs: [<tf.Tensor 'prefix/generator_1/g_h4/conv2d_transpose:0' shape=(1, 256, 256, 3) dtype=float32>]
name: prefix/generator_1/g_h4/BiasAdd | type: BiasAdd | outputs: [<tf.Tensor 'prefix/generator_1/g_h4/BiasAdd:0' shape=(1, 256, 256, 3) dtype=float32>]
name: prefix/generator_1/g_h4/Reshape/shape | type: Const | outputs: [<tf.Tensor 'prefix/generator_1/g_h4/Reshape/shape:0' shape=(4,) dtype=int32>]
name: prefix/generator_1/g_h4/Reshape | type: Reshape | outputs: [<tf.Tensor 'prefix/generator_1/g_h4/Reshape:0' shape=(1, 256, 256, 3) dtype=float32>]
name: prefix/generator_1/Tanh | type: Tanh | outputs: [<tf.Tensor 'prefix/generator_1/Tanh:0' shape=(1, 256, 256, 3) dtype=float32>]
If I understand it correctly, the layer of type Placeholder is the input and the tanh is the output.
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Related Issues (20)
- input _fname_pattern"*.jpg" Synatx Error: Invalid Syntax error in line 91 in main.py
- Why the kernel size of discriminator is 4?
- raise Exception("[!] Entire dataset size is less than the configured batch_size") Exception: [!] Entire dataset size is less than the configured batch_size
- why my model is not converge after 300 epochs HOT 1
- checkpoint not found HOT 2
- Solved some problems in my repo/解决了一些问题
- raise Exception("Checkpoint not found in " + FLAGS.checkpoint_dir) Exception: Checkpoint not found in ./out\20200526.133337 - data - retina\checkpoint HOT 5
- Training and Test generating black squares HOT 2
- There are two bugs in the transform function in the utils.py HOT 2
- How to save discriminator network? HOT 2
- Can't create checkpoint
- cannot generate when testing
- failed to teat
- failed to test HOT 1
- NameError：name 'PIL' is not defined HOT 1
- ValueError: could not broadcast input array from shape (1,2048) into shape (98,1024) HOT 2
- TypeError: 'NoneType' object is not subscriptable
- How to generate larger images? HOT 1
- InvalidArgumentError (see above for traceback): Nan in summary histogram for: HistogramSummary_2 [[Node: HistogramSummary_2 = HistogramSummary[T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/cpu:0"](HistogramSummary_2/tag, discriminator_1/Sigmoid)]] HOT 1
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from dcgan-tensorflow.