Fixed merge conflicts + rebase (6bc0d70b) · Commits · 钟慕尧 / deepchem

deepchem/models/tests/test_layers.py

+90 −1

Original line number	Diff line number	Diff line
		@@ -618,6 +618,95 @@ def test_scale_norm():
		assert torch.allclose(result1, output_ar)


		@pytest.mark.torch
		def test_multi_headed_mat_attention():
		"""Test invoking MultiHeadedMATAttention."""
		from rdkit import Chem
		torch.manual_seed(0)
		input_smile = "CC"
		mol = Chem.MolFromSmiles(input_smile)
		adj_matrix = Chem.GetAdjacencyMatrix(mol)
		distance_matrix = Chem.GetDistanceMatrix(mol)
		layer = torch_layers.MultiHeadedMATAttention(
		dist_kernel='softmax',
		lambda_attention=0.33,
		lambda_distance=0.33,
		h=2,
		hsize=2,
		dropout_p=0.0)
		input_tensor = torch.tensor([[1., 2.], [5., 6.]])
		mask = torch.tensor([[1., 1.], [1., 1.]])
		result = layer(input_tensor, input_tensor, input_tensor, mask, adj_matrix,
		distance_matrix, 0.0)
		output_ar = torch.tensor([[[0.0492, -0.0792], [-0.9971, -0.3172],
		[0.0492, -0.0792], [-0.9971, -0.3172]],
		[[0.8671, 0.1069], [-3.4075, -0.8656],
		[0.8671, 0.1069], [-3.4075, -0.8656]]])
		assert torch.allclose(result, output_ar, rtol=1e-3)


		@pytest.mark.torch
		def test_position_wise_feed_forward():
		"""Test invoking PositionwiseFeedForward."""
		torch.manual_seed(0)
		input_ar = torch.tensor([[1., 2.], [5., 6.]])
		layer = torch_layers.PositionwiseFeedForward(
		d_input=2,
		d_hidden=2,
		d_output=2,
		activation='relu',
		n_layers=1,
		dropout_p=0.0)
		result = layer(input_ar)
		output_ar = torch.tensor([[0.4810, 0.0000], [1.9771, 0.0000]])
		assert torch.allclose(result, output_ar, rtol=1e-4)


		@pytest.mark.torch
		def test_sub_layer_connection():
		"""Test invoking SublayerConnection."""
		torch.manual_seed(0)
		input_ar = torch.tensor([[1., 2.], [5., 6.]])
		layer = torch_layers.SublayerConnection(2, 0.0)
		result = layer(input_ar, input_ar)
		output_ar = torch.tensor([[2.0027e-05, 3.0000e+00], [4.0000e+00, 7.0000e+00]])
		assert torch.allclose(result, output_ar)


		@pytest.mark.torch
		def test_mat_encoder_layer():
		"""Test invoking MATEncoderLayer."""
		torch.manual_seed(0)
		from rdkit import Chem
		input_ar = torch.Tensor([[1., 2.], [5., 6.]])
		mask = torch.Tensor([[1., 1.], [1., 1.]])
		mol = Chem.MolFromSmiles("CC")
		adj_matrix = Chem.GetAdjacencyMatrix(mol)
		distance_matrix = Chem.GetDistanceMatrix(mol)
		layer = torch_layers.MATEncoderLayer(
		dist_kernel='softmax',
		lambda_attention=0.33,
		lambda_distance=0.33,
		h=2,
		sa_hsize=2,
		sa_dropout_p=0.0,
		output_bias=True,
		d_input=2,
		d_hidden=2,
		d_output=2,
		activation='relu',
		n_layers=2,
		ff_dropout_p=0.0,
		encoder_hsize=2,
		encoder_dropout_p=0.0)
		result = layer(input_ar, mask, adj_matrix, distance_matrix, 0.0)
		output_ar = torch.tensor([[[0.9988, 2.0012], [-0.9999, 3.9999],
		[0.9988, 2.0012], [-0.9999, 3.9999]],
		[[5.0000, 6.0000], [3.0000, 8.0000],
		[5.0000, 6.0000], [3.0000, 8.0000]]])
		assert torch.allclose(result, output_ar, rtol=1e-4)


		@pytest.mark.torch
		def test_mat_embedding():
		"""Test invoking MATEmbedding."""

deepchem/models/torch_models/layers.py

+473 −16

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docs/source/api_reference/layers.rst

+12 −1

Original line number	Diff line number	Diff line
		@@ -125,6 +125,18 @@ Torch Layers
		.. autoclass:: deepchem.models.torch_models.layers.ScaleNorm
		:members:

		.. autoclass:: deepchem.models.torch_models.layers.MATEncoderLayer
		:members:

		.. autoclass:: deepchem.models.torch_models.layers.MultiHeadedMATAttention
		:members:

		.. autoclass:: deepchem.models.torch_models.layers.SublayerConnection
		:members:

		.. autoclass:: deepchem.models.torch_models.layers.PositionwiseFeedForward
		:members:

		.. autoclass:: deepchem.models.torch_models.layers.MATEmbedding
		:members:

		@@ -138,4 +150,3 @@ Jax Layers

		.. autoclass:: deepchem.models.jax_models.layers.Linear
		:members:

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