Given this code snippet for training an RNN text generator, what will be the shape of the input data X if the vocabulary size is 5000, sequence length is 20, and batch size is 32?

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NLP - Text Generation

Given this code snippet for training an RNN text generator, what will be the shape of the input data X if the vocabulary size is 5000, sequence length is 20, and batch size is 32?

model = Sequential()
model.add(Embedding(input_dim=5000, output_dim=50, input_length=20))
model.add(SimpleRNN(100))
model.add(Dense(5000, activation='softmax'))

X = np.random.randint(0, 5000, (32, 20))

A(20, 32)

B(32, 20)

C(32, 50)

D(5000, 20)

Step-by-Step Solution

Solution:

Step 1: Understand input shape for embedding
The input to the embedding layer is a 2D array: (batch_size, sequence_length).
Step 2: Check given data shape
X is created with shape (32, 20), matching batch size 32 and sequence length 20.
Final Answer:
(32, 20) -> Option B
Quick Check:
Input shape = (batch_size, sequence_length) = (32, 20) [OK]

Quick Trick: Input shape = batch size by sequence length [OK]

Common Mistakes:

MISTAKES

Confusing embedding output shape with input shape
Swapping batch size and sequence length
Assuming embedding changes input shape

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Given this code snippet for training an RNN text generator, what will be the shape of the input data X if the vocabulary size is 5000, sequence length is 20, and batch size is 32?

Step 1: Understand input shape for embedding

Step 2: Check given data shape

Final Answer:

Quick Check:

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