def test_tf_multi_output_int(self):
model = fe.build(model_fn=multi_layer_tf_model, optimizer_fn="adam")
op = ModelOp(inputs='x',
outputs=['y', 'embedding'],
model=model,
intermediate_layers=1)
op.build(framework='tf', device=None)
with self.subTest("Eager"):
y, embedding = op.forward(data=self.tf_input_data_big,
state=self.state)
self.assertTrue(np.allclose(y.numpy(), self.output_big, atol=1e-4))
self.assertTrue(
np.allclose(embedding.numpy(),
self.embedding_output,
atol=1e-4))
forward_fn = tf.function(op.forward)
with self.subTest("Static Call 1"):
y, embedding = forward_fn(data=self.tf_input_data_big,
state=self.state)
self.assertTrue(np.allclose(y.numpy(), self.output_big, atol=1e-4))
self.assertTrue(
np.allclose(embedding.numpy(),
self.embedding_output,
atol=1e-4))
with self.subTest("Static Call 2"):
y, embedding = forward_fn(data=self.tf_input_data_big,
state=self.state)
self.assertTrue(np.allclose(y.numpy(), self.output_big, atol=1e-4))
self.assertTrue(
np.allclose(embedding.numpy(),
self.embedding_output,
atol=1e-4))
def test_torch_input(self):
model = fe.build(model_fn=OneLayerTorchModel, optimizer_fn="adam")
self.torch_input_data = self.torch_input_data.to(
"cuda:0" if torch.cuda.is_available() else "cpu")
model.to("cuda:0" if torch.cuda.is_available() else "cpu")
op = ModelOp(inputs='x', outputs='x', model=model)
op.build(framework='torch',
device=torch.device(
"cuda:0" if torch.cuda.is_available() else "cpu"))
output = op.forward(data=self.torch_input_data, state=self.state)
output = output.to("cpu")
self.assertTrue(is_equal(output.detach().numpy(), self.output))
def test_tf_input(self):
model = fe.build(model_fn=one_layer_tf_model, optimizer_fn="adam")
op = ModelOp(inputs='x', outputs='x', model=model)
op.build(framework='tf', device=None)
with self.subTest("Eager"):
output = op.forward(data=self.tf_input_data, state=self.state)
self.assertTrue(is_equal(output.numpy(), self.output))
forward_fn = tf.function(op.forward)
with self.subTest("Static Call 1"):
output = forward_fn(data=self.tf_input_data, state=self.state)
self.assertTrue(is_equal(output.numpy(), self.output))
with self.subTest("Static Call 2"):
output = forward_fn(data=self.tf_input_data, state=self.state)
self.assertTrue(is_equal(output.numpy(), self.output))
def test_torch_multi_output_int(self):
model = fe.build(model_fn=MultiLayerTorchModel, optimizer_fn="adam")
self.torch_input_data_big = self.torch_input_data_big.to(
"cuda:0" if torch.cuda.is_available() else "cpu")
model.to("cuda:0" if torch.cuda.is_available() else "cpu")
op = ModelOp(inputs='x',
outputs=['y', 'embedding'],
model=model,
intermediate_layers=1)
op.build(framework='torch',
device=torch.device(
"cuda:0" if torch.cuda.is_available() else "cpu"))
y, embedding = op.forward(data=self.torch_input_data_big,
state=self.state)
y = y.to("cpu")
embedding = embedding.to('cpu')
self.assertTrue(
np.allclose(y.detach().numpy(), self.output_big, atol=1e-4))
self.assertTrue(
np.allclose(embedding.detach().numpy(),
self.embedding_output,
atol=1e-4))