icefall/icefall/rnn_lm/test_model.py

70 lines
1.8 KiB
Python
Executable File

#!/usr/bin/env python3
# Copyright (c) 2021 Xiaomi Corporation (authors: Fangjun Kuang)
#
# See ../../../../LICENSE for clarification regarding multiple authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import torch
from rnn_lm.model import RnnLmModel
def test_rnn_lm_model():
vocab_size = 4
model = RnnLmModel(
vocab_size=vocab_size, embedding_dim=10, hidden_dim=10, num_layers=2
)
x = torch.tensor(
[
[1, 3, 2, 2],
[1, 2, 2, 0],
[1, 2, 0, 0],
]
)
y = torch.tensor(
[
[3, 2, 2, 1],
[2, 2, 1, 0],
[2, 1, 0, 0],
]
)
lengths = torch.tensor([4, 3, 2])
nll_loss = model(x, y, lengths)
print(nll_loss)
"""
tensor([[1.1180, 1.3059, 1.2426, 1.7773],
[1.4231, 1.2783, 1.7321, 0.0000],
[1.4231, 1.6752, 0.0000, 0.0000]], grad_fn=<ViewBackward>)
"""
def test_rnn_lm_model_tie_weights():
model = RnnLmModel(
vocab_size=10,
embedding_dim=10,
hidden_dim=10,
num_layers=2,
tie_weights=True,
)
assert model.input_embedding.weight is model.output_linear.weight
def main():
test_rnn_lm_model()
test_rnn_lm_model_tie_weights()
if __name__ == "__main__":
torch.manual_seed(20211122)
main()