def test_openai_can_run_with_no_offsets(self):
params = Params({
"transformer": {
"model_path": "allennlp/tests/fixtures/openai_transformer/transformer_small.tar.gz",
"embedding_dim": 10,
"num_heads": 2,
"num_layers": 2,
"vocab_size": 50,
"n_ctx": 50
},
})
embedder = OpenaiTransformerEmbedder.from_params(params)
training_tensors = self._get_training_tensors()
output = embedder(training_tensors['tokens']['openai_transformer'])
assert list(output.shape) == [2, 2, 10]
def test_openai_can_run_with_no_offsets(self):
params = Params({
"transformer": {
"model_path":
"allennlp/tests/fixtures/openai_transformer/transformer_small.tar.gz",
"embedding_dim": 10,
"num_heads": 2,
"num_layers": 2,
"vocab_size": 50,
"n_ctx": 50
},
})
embedder = OpenaiTransformerEmbedder.from_params(params)
training_tensors = self._get_training_tensors()
output = embedder(training_tensors['tokens']['openai_transformer'])
assert list(output.shape) == [2, 2, 10]
def test_openai_can_run_with_top_layer(self):
params = Params({
"transformer": {
"model_path":
"allennlp/tests/fixtures/openai_transformer/transformer_small.tar.gz",
"embedding_dim": 10,
"num_heads": 2,
"num_layers": 2,
"vocab_size": 50,
"n_ctx": 50,
},
"top_layer_only": True,
})
embedder = OpenaiTransformerEmbedder.from_params(params)
training_tensors = self._get_training_tensors()
output = embedder(**training_tensors["tokens"]["openai_transformer"])
assert list(output.shape) == [2, 7, 10]