Row 29090

Row ID: 29090 | Dataset Entry | Axioma AXP Content Repository

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I'm trying to create a model using the pre-trained BERT model from [kaggle](https://www.kaggle.com/models/tensorflow/bert/tensorFlow2/en-uncased-l-12-h-768-a-12). The model architecture is given below:

import tensorflow_hub as hub import tensorflow_text as text

import numpy as np from tensorflow.keras.optimizers import SGD from tensorflow.keras.models import Model from tensorflow.keras.layers import Input, Dense

def build_model(bert_layer, preprocessor): text_input = Input(shape=(), dtype=tf.string) encoder_inputs = preprocessor(text_input) pooled_output, sequence_output = bert_layer(encoder_inputs) clf_output = sequence_output[:, 0, :] out = Dense(1, activation='sigmoid')(clf_output) model = Model(inputs=text_input, outputs=out) optimizer = SGD(learning_rate=self.lr, momentum=0.8) # model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy']) return model

The error is given below:

ValueError: Exception encountered when calling layer 'keras\_layer\_2' (type KerasLayer).

A KerasTensor is symbolic: it's a placeholder for a shape an a dtype. It doesn't have any actual numerical value. You cannot convert it to a NumPy array.

Call arguments received by layer 'keras\_layer\_2' (type KerasLayer):

• inputs=<KerasTensor shape=(None,), dtype=string, sparse=None, name=keras\_tensor\_1>

• training=None

I believe a numpy function is being called on the Input layer, which does not have any values. Is there any way to fix this. Is this due to dependency version mis match?

Thanks!

FieldValue
text I'm trying to create a model using the pre-trained BERT model from [kaggle](https://www.kaggle.com/models/tensorflow/bert/tensorFlow2/en-uncased-l-12-h-768-a-12). The model architecture is given below: import tensorflow_hub as hub import tensorflow_text as text import numpy as np from tensorflow.keras.optimizers import SGD from tensorflow.keras.models import Model from tensorflow.keras.layers import Input, Dense def build_model(bert_layer, preprocessor): …
label r/tensorflow
dataType post
communityName r/tensorflow
datetime 2024-05-21
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url_encoded Z0FBQUFBQm5Lak9VUGxZajVXcUcxamxwUUs5ZzNnUU5mcnpERGh6MFBNTWhMQ2p3aFZVajZ3NWpyTU9pdndJUWgwUmk2Y2dmYjkxOGREYnMxV1hsZW53TkFPaXZaLWFobGdpVTBJazd2VFBHa3I2RkJRZmN4QzBoWW45N082eUx3NVZ5VUlLVkNPMm9ldTBqNVNqRjBVcGllSUtKdXNLaFpJZXBDdS1OcVpyV0RRZkI1VDVUSHRocU43aFViVWVuc1J1eS00U1g5dHQyV0NBVlFWcFpvTXhlOE8xdzVhVTNsUT09

Raw Record

{
  "text": "I'm trying to create a model using the pre-trained BERT model from [kaggle](https://www.kaggle.com/models/tensorflow/bert/tensorFlow2/en-uncased-l-12-h-768-a-12). The model architecture is given below:\n\n    import tensorflow_hub as hub\n    import tensorflow_text as text\n\n    import numpy as np\n    from tensorflow.keras.optimizers import SGD\n    from tensorflow.keras.models import Model\n    from tensorflow.keras.layers import Input, Dense\n    \n\n    \n    def build_model(bert_layer, preprocessor):\n    \n        text_input = Input(shape=(), dtype=tf.string)\n    \n        encoder_inputs = preprocessor(text_input)\n        pooled_output, sequence_output = bert_layer(encoder_inputs)   \n        clf_output = sequence_output[:, 0, :]\n        out = Dense(1, activation='sigmoid')(clf_output)\n        \n        model = Model(inputs=text_input, outputs=out)\n        optimizer = SGD(learning_rate=self.lr, momentum=0.8)\n        # model.compile(loss='binary_crossentropy', optimizer=optimizer, metrics=['accuracy'])\n        \n        return model\n\nThe error is given below:\n\nValueError: Exception encountered when calling layer 'keras\\_layer\\_2' (type KerasLayer).\n\nA KerasTensor is symbolic: it's a placeholder for a shape an a dtype. It doesn't have any actual numerical value. You cannot convert it to a NumPy array.\n\nCall arguments received by layer 'keras\\_layer\\_2' (type KerasLayer):\n\n  • inputs=<KerasTensor shape=(None,), dtype=string, sparse=None, name=keras\\_tensor\\_1>\n\n  • training=None\n\nI believe a numpy function is being called on the Input layer, which does not have any values. Is there any way to fix this. Is this due to dependency version mis match?\n\nThanks!",
  "label": "r/tensorflow",
  "dataType": "post",
  "communityName": "r/tensorflow",
  "datetime": "2024-05-21",
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}
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