def test_mlp_input_signatures(self):
mlp_block = mlp.MLP(d_hidden=32, n_output_classes=10)
relu = tl.Relu()
mlp_and_relu = tl.Serial(mlp_block, relu)
# Check for correct shapes entering and exiting the mlp_block.
mlp_and_relu.input_signature = ShapeDtype((3, 28, 28, 1))
self.assertEqual(mlp_block.input_signature, ShapeDtype((3, 28, 28, 1)))
self.assertEqual(relu.input_signature, ShapeDtype((3, 10)))
def test_mlp_input_signatures(self):
mlp_layer = mlp.MLP(d_hidden=32, n_output_classes=10)
relu = tl.Relu()
mlp_and_relu = tl.Serial(
mlp_layer,
relu,
)
x = np.ones((3, 28, 28, 1)).astype(np.float32)
input_signature = shapes.signature(x)
mlp_and_relu.init(input_signature)
# Check for correct shapes entering and exiting the mlp_block.
mlp_and_relu._set_input_signature_recursive(input_signature)
self.assertEqual(mlp_layer.input_signature, input_signature)
self.assertEqual(relu.input_signature, shapes.ShapeDtype((3, 10)))
def test_mlp_forward_shape(self):
"""Run the MLP model forward and check output shape."""
input_signature = ShapeDtype((3, 28, 28, 1))
model = mlp.MLP(d_hidden=32, n_output_classes=10)
final_shape = tl.check_shape_agreement(model, input_signature)
self.assertEqual((3, 10), final_shape)
def test_mlp_forward_shape(self):
model = mlp.MLP(layer_widths=(32, 16, 8))
x = np.ones((7, 28, 28, 3)).astype(np.float32)
_, _ = model.init(shapes.signature(x))
y = model(x)
self.assertEqual(y.shape, (7, 8))
def test_mlp_forward_shape(self):
model = mlp.MLP(d_hidden=32, n_output_classes=10)
x = np.ones((3, 28, 28, 1)).astype(np.float32)
_, _ = model.init(shapes.signature(x))
y = model(x)
self.assertEqual(y.shape, (3, 10))
