update demos to use protobuf format models

transcranial · Nov 10, 2017 · 347d3ef · 347d3ef
1 parent 493ff3b
commit 347d3ef
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Showing 15 changed files with 452 additions and 793 deletions.
diff --git a/demos/src/components/models/ImdbBidirectionalLstm.vue b/demos/src/components/models/ImdbBidirectionalLstm.vue
@@ -63,19 +63,12 @@ import findIndex from 'lodash/findIndex'
 import ops from 'ndarray-ops'
 import Tensor from '../../../../src/Tensor'
 
-const MODEL_FILEPATHS_DEV = {
-  model: '/demos/data/imdb_bidirectional_lstm/imdb_bidirectional_lstm.json',
-  weights: '/demos/data/imdb_bidirectional_lstm/imdb_bidirectional_lstm_weights.buf',
-  metadata: '/demos/data/imdb_bidirectional_lstm/imdb_bidirectional_lstm_metadata.json'
+const MODEL_CONFIG = {
+  filepath:
+    process.env.NODE_ENV === 'production'
+      ? 'https://transcranial.github.io/keras-js-demos-data/imdb_bidirectional_lstm/imdb_bidirectional_lstm.bin'
+      : '/demos/data/imdb_bidirectional_lstm/imdb_bidirectional_lstm.bin'
 }
-const MODEL_FILEPATHS_PROD = {
-  model: 'https://transcranial.github.io/keras-js-demos-data/imdb_bidirectional_lstm/imdb_bidirectional_lstm.json',
-  weights:
-    'https://transcranial.github.io/keras-js-demos-data/imdb_bidirectional_lstm/imdb_bidirectional_lstm_weights.buf',
-  metadata:
-    'https://transcranial.github.io/keras-js-demos-data/imdb_bidirectional_lstm/imdb_bidirectional_lstm_metadata.json'
-}
-const MODEL_CONFIG = { filepaths: process.env.NODE_ENV === 'production' ? MODEL_FILEPATHS_PROD : MODEL_FILEPATHS_DEV }
 
 const ADDITIONAL_DATA_FILEPATHS_DEV = {
   wordIndex: '/demos/data/imdb_bidirectional_lstm/imdb_dataset_word_index_top20000.json',
@@ -102,14 +95,14 @@ const INDEX_FROM = 3
 
 // network layers
 const ARCHITECTURE_DIAGRAM_LAYERS = [
-  { name: 'embedding_2', className: 'Embedding', details: '200 time steps, dims 20000 -> 64' },
+  { name: 'embedding_1', className: 'Embedding', details: '200 time steps, dims 20000 -> 64' },
   {
-    name: 'bidirectional_2',
+    name: 'bidirectional_1',
     className: 'Bidirectional [LSTM]',
     details: '200 time steps, dims 64 -> 32, concat merge, tanh activation, hard sigmoid recurrent activation'
   },
-  { name: 'dropout_2', className: 'Dropout', details: 'p=0.5 (active during training)' },
-  { name: 'dense_2', className: 'Dense', details: 'output dims 1, sigmoid activation' }
+  { name: 'dropout_1', className: 'Dropout', details: 'p=0.5 (active during training)' },
+  { name: 'dense_1', className: 'Dense', details: 'output dims 1, sigmoid activation' }
 ]
 
 export default {
@@ -172,6 +165,7 @@ export default {
       this.inputText = ''
       this.inputTextParsed = []
       this.output = new Float32Array(1)
+      this.isSampleText = false
     },
     loadAdditionalData: function() {
       this.modelLoading = true
@@ -253,9 +247,9 @@ export default {
       })
     }, 200),
     stepwiseCalc: function() {
-      const fcLayer = this.model.modelLayersMap.get('dense_2')
-      const forwardHiddenStates = this.model.modelLayersMap.get('bidirectional_2').forwardLayer.hiddenStateSequence
-      const backwardHiddenStates = this.model.modelLayersMap.get('bidirectional_2').backwardLayer.hiddenStateSequence
+      const fcLayer = this.model.modelLayersMap.get('dense_1')
+      const forwardHiddenStates = this.model.modelLayersMap.get('bidirectional_1').forwardLayer.hiddenStateSequence
+      const backwardHiddenStates = this.model.modelLayersMap.get('bidirectional_1').backwardLayer.hiddenStateSequence
       const forwardDim = forwardHiddenStates.tensor.shape[1]
       const backwardDim = backwardHiddenStates.tensor.shape[1]
 

diff --git a/demos/src/components/models/InceptionV3.vue b/demos/src/components/models/InceptionV3.vue
@@ -95,17 +95,12 @@ import * as utils from '../../utils'
 import { IMAGE_URLS } from '../../data/sample-image-urls'
 import { ARCHITECTURE_DIAGRAM, ARCHITECTURE_CONNECTIONS } from '../../data/inception-v3-arch'
 
-const MODEL_FILEPATHS_DEV = {
-  model: '/demos/data/inception_v3/inception_v3.json',
-  weights: '/demos/data/inception_v3/inception_v3_weights.buf',
-  metadata: '/demos/data/inception_v3/inception_v3_metadata.json'
+const MODEL_CONFIG = {
+  filepath:
+    process.env.NODE_ENV === 'production'
+      ? 'https://transcranial.github.io/keras-js-demos-data/inception_v3/inception_v3.bin'
+      : '/demos/data/inception_v3/inception_v3.bin'
 }
-const MODEL_FILEPATHS_PROD = {
-  model: 'https://transcranial.github.io/keras-js-demos-data/inception_v3/inception_v3.json',
-  weights: 'https://transcranial.github.io/keras-js-demos-data/inception_v3/inception_v3_weights.buf',
-  metadata: 'https://transcranial.github.io/keras-js-demos-data/inception_v3/inception_v3_metadata.json'
-}
-const MODEL_CONFIG = { filepaths: process.env.NODE_ENV === 'production' ? MODEL_FILEPATHS_PROD : MODEL_FILEPATHS_DEV }
 
 export default {
   props: ['hasWebGL'],

diff --git a/demos/src/components/models/MnistAcgan.vue b/demos/src/components/models/MnistAcgan.vue
@@ -56,17 +56,12 @@ import * as utils from '../../utils'
 import filter from 'lodash/filter'
 import { ARCHITECTURE_DIAGRAM, ARCHITECTURE_CONNECTIONS } from '../../data/mnist-acgan-arch'
 
-const MODEL_FILEPATHS_DEV = {
-  model: '/demos/data/mnist_acgan/mnist_acgan.json',
-  weights: '/demos/data/mnist_acgan/mnist_acgan_weights.buf',
-  metadata: '/demos/data/mnist_acgan/mnist_acgan_metadata.json'
+const MODEL_CONFIG = {
+  filepath:
+    process.env.NODE_ENV === 'production'
+      ? 'https://transcranial.github.io/keras-js-demos-data/mnist_acgan/mnist_acgan.bin'
+      : '/demos/data/mnist_acgan/mnist_acgan.bin'
 }
-const MODEL_FILEPATHS_PROD = {
-  model: 'https://transcranial.github.io/keras-js-demos-data/mnist_acgan/mnist_acgan.json',
-  weights: 'https://transcranial.github.io/keras-js-demos-data/mnist_acgan/mnist_acgan_weights.buf',
-  metadata: 'https://transcranial.github.io/keras-js-demos-data/mnist_acgan/mnist_acgan_metadata.json'
-}
-const MODEL_CONFIG = { filepaths: process.env.NODE_ENV === 'production' ? MODEL_FILEPATHS_PROD : MODEL_FILEPATHS_DEV }
 
 export default {
   props: ['hasWebGL'],

diff --git a/demos/src/components/models/MnistCnn.vue b/demos/src/components/models/MnistCnn.vue
@@ -84,17 +84,12 @@ import debounce from 'lodash/debounce'
 import range from 'lodash/range'
 import * as utils from '../../utils'
 
-const MODEL_FILEPATHS_DEV = {
-  model: '/demos/data/mnist_cnn/mnist_cnn.json',
-  weights: '/demos/data/mnist_cnn/mnist_cnn_weights.buf',
-  metadata: '/demos/data/mnist_cnn/mnist_cnn_metadata.json'
+const MODEL_CONFIG = {
+  filepath:
+    process.env.NODE_ENV === 'production'
+      ? 'https://transcranial.github.io/keras-js-demos-data/mnist_cnn/mnist_cnn.bin'
+      : '/demos/data/mnist_cnn/mnist_cnn.bin'
 }
-const MODEL_FILEPATHS_PROD = {
-  model: 'https://transcranial.github.io/keras-js-demos-data/mnist_cnn/mnist_cnn.json',
-  weights: 'https://transcranial.github.io/keras-js-demos-data/mnist_cnn/mnist_cnn_weights.buf',
-  metadata: 'https://transcranial.github.io/keras-js-demos-data/mnist_cnn/mnist_cnn_metadata.json'
-}
-const MODEL_CONFIG = { filepaths: process.env.NODE_ENV === 'production' ? MODEL_FILEPATHS_PROD : MODEL_FILEPATHS_DEV }
 
 const LAYER_DISPLAY_CONFIG = {
   conv2d_1: { heading: '32 3x3 filters, padding valid, 1x1 strides', scalingFactor: 2 },

diff --git a/demos/src/components/models/MnistVae.vue b/demos/src/components/models/MnistVae.vue
@@ -82,26 +82,21 @@
 import _ from 'lodash'
 import * as utils from '../../utils'
 
-const MODEL_FILEPATHS_DEV = {
-  model: '/demos/data/mnist_vae/mnist_vae.json',
-  weights: '/demos/data/mnist_vae/mnist_vae_weights.buf',
-  metadata: '/demos/data/mnist_vae/mnist_vae_metadata.json'
+const MODEL_CONFIG = {
+  filepath:
+    process.env.NODE_ENV === 'production'
+      ? 'https://transcranial.github.io/keras-js-demos-data/mnist_vae/mnist_vae.bin'
+      : '/demos/data/mnist_vae/mnist_vae.bin'
 }
-const MODEL_FILEPATHS_PROD = {
-  model: 'https://transcranial.github.io/keras-js-demos-data/mnist_vae/mnist_vae.json',
-  weights: 'https://transcranial.github.io/keras-js-demos-data/mnist_vae/mnist_vae_weights.buf',
-  metadata: 'https://transcranial.github.io/keras-js-demos-data/mnist_vae/mnist_vae_metadata.json'
-}
-const MODEL_CONFIG = { filepaths: process.env.NODE_ENV === 'production' ? MODEL_FILEPATHS_PROD : MODEL_FILEPATHS_DEV }
 
 const LAYER_DISPLAY_CONFIG = {
-  dense_19: { heading: 'input dimensions = 2, output dimensions = 128, ReLU activation', scalingFactor: 2 },
-  dense_20: { heading: 'ReLU activation, output dimensions = 25088 (64 x 14 x 14)', scalingFactor: 2 },
-  reshape_7: { heading: '', scalingFactor: 2 },
-  conv2d_transpose_19: { heading: '64 3x3 filters, padding same, 1x1 strides, ReLU activation', scalingFactor: 2 },
-  conv2d_transpose_20: { heading: '64 3x3 filters, padding same, 1x1 strides, ReLU activation', scalingFactor: 2 },
-  conv2d_transpose_21: { heading: '64 2x2 filters, padding valid, 2x2 strides, ReLU activation', scalingFactor: 2 },
-  conv2d_15: { heading: '1 2x2 filters, padding same, 1x1 strides, sigmoid activation', scalingFactor: 2 }
+  dense_6: { heading: 'input dimensions = 2, output dimensions = 128, ReLU activation', scalingFactor: 2 },
+  dense_7: { heading: 'ReLU activation, output dimensions = 25088 (64 x 14 x 14)', scalingFactor: 2 },
+  reshape_2: { heading: '', scalingFactor: 2 },
+  conv2d_transpose_4: { heading: '64 3x3 filters, padding same, 1x1 strides, ReLU activation', scalingFactor: 2 },
+  conv2d_transpose_5: { heading: '64 3x3 filters, padding same, 1x1 strides, ReLU activation', scalingFactor: 2 },
+  conv2d_transpose_6: { heading: '64 2x2 filters, padding valid, 2x2 strides, ReLU activation', scalingFactor: 2 },
+  conv2d_6: { heading: '1 2x2 filters, padding same, 1x1 strides, sigmoid activation', scalingFactor: 2 }
 }
 
 export default {
@@ -207,9 +202,9 @@ export default {
       { leading: true, trailing: true }
     ),
     runModel: function() {
-      const inputData = { input_7: new Float32Array(this.inputCoordinates) }
+      const inputData = { input_2: new Float32Array(this.inputCoordinates) }
       this.model.predict(inputData).then(outputData => {
-        this.output = outputData['conv2d_15']
+        this.output = outputData['conv2d_6']
         this.drawOutput()
         this.getIntermediateOutputs()
       })

diff --git a/demos/src/components/models/Resnet50.vue b/demos/src/components/models/Resnet50.vue
@@ -95,17 +95,12 @@ import * as utils from '../../utils'
 import { IMAGE_URLS } from '../../data/sample-image-urls'
 import { ARCHITECTURE_DIAGRAM, ARCHITECTURE_CONNECTIONS } from '../../data/resnet50-arch'
 
-const MODEL_FILEPATHS_DEV = {
-  model: '/demos/data/resnet50/resnet50.json',
-  weights: '/demos/data/resnet50/resnet50_weights.buf',
-  metadata: '/demos/data/resnet50/resnet50_metadata.json'
+const MODEL_CONFIG = {
+  filepath:
+    process.env.NODE_ENV === 'production'
+      ? 'https://transcranial.github.io/keras-js-demos-data/resnet50/resnet50.bin'
+      : '/demos/data/resnet50/resnet50.bin'
 }
-const MODEL_FILEPATHS_PROD = {
-  model: 'https://transcranial.github.io/keras-js-demos-data/resnet50/resnet50.json',
-  weights: 'https://transcranial.github.io/keras-js-demos-data/resnet50/resnet50_weights.buf',
-  metadata: 'https://transcranial.github.io/keras-js-demos-data/resnet50/resnet50_metadata.json'
-}
-const MODEL_CONFIG = { filepaths: process.env.NODE_ENV === 'production' ? MODEL_FILEPATHS_PROD : MODEL_FILEPATHS_DEV }
 
 export default {
   props: ['hasWebGL'],

diff --git a/demos/src/components/models/SqueezenetV1.vue b/demos/src/components/models/SqueezenetV1.vue
@@ -95,17 +95,12 @@ import * as utils from '../../utils'
 import { IMAGE_URLS } from '../../data/sample-image-urls'
 import { ARCHITECTURE_DIAGRAM, ARCHITECTURE_CONNECTIONS } from '../../data/squeezenet-v1.1-arch'
 
-const MODEL_FILEPATHS_DEV = {
-  model: '/demos/data/squeezenet_v1.1/squeezenet_v1.1.json',
-  weights: '/demos/data/squeezenet_v1.1/squeezenet_v1.1_weights.buf',
-  metadata: '/demos/data/squeezenet_v1.1/squeezenet_v1.1_metadata.json'
+const MODEL_CONFIG = {
+  filepath:
+    process.env.NODE_ENV === 'production'
+      ? 'https://transcranial.github.io/keras-js-demos-data/squeezenet_v1.1/squeezenet_v1.1.bin'
+      : '/demos/data/squeezenet_v1.1/squeezenet_v1.1.bin'
 }
-const MODEL_FILEPATHS_PROD = {
-  model: 'https://transcranial.github.io/keras-js-demos-data/squeezenet_v1.1/squeezenet_v1.1.json',
-  weights: 'https://transcranial.github.io/keras-js-demos-data/squeezenet_v1.1/squeezenet_v1.1_weights.buf',
-  metadata: 'https://transcranial.github.io/keras-js-demos-data/squeezenet_v1.1/squeezenet_v1.1_metadata.json'
-}
-const MODEL_CONFIG = { filepaths: process.env.NODE_ENV === 'production' ? MODEL_FILEPATHS_PROD : MODEL_FILEPATHS_DEV }
 
 export default {
   props: ['hasWebGL'],