From 43c06f5863a3374e2cf0b7075bcfd79ecf2d4dfd Mon Sep 17 00:00:00 2001 From: Ishaan Mathur Date: Wed, 22 Oct 2025 14:27:54 +0000 Subject: [PATCH 1/4] addressing esm issue 279 and 265 --- cookbook/tutorials/2_embed.ipynb | 147 ++++++++--------------- esm/__init__.py | 2 +- esm/sdk/api.py | 7 +- esm/sdk/forge.py | 2 + esm/utils/structure/molecular_complex.py | 3 +- esm/utils/structure/protein_chain.py | 4 +- pixi.lock | 103 +++++++++------- pyproject.toml | 4 +- tests/Makefile | 6 +- 9 files changed, 131 insertions(+), 147 deletions(-) diff --git a/cookbook/tutorials/2_embed.ipynb b/cookbook/tutorials/2_embed.ipynb index 61fdb397..a99a215c 100644 --- a/cookbook/tutorials/2_embed.ipynb +++ b/cookbook/tutorials/2_embed.ipynb @@ -20,18 +20,7 @@ "cell_type": "code", "execution_count": null, "metadata": {}, - "outputs": [ - { - "ename": "", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[1;31mRunning cells with 'default (Python 3.11.11)' requires the ipykernel package.\n", - "\u001b[1;31mRun the following command to install 'ipykernel' into the Python environment. \n", - "\u001b[1;31mCommand: '/home/wxi/wt4/.pixi/envs/default/bin/python -m pip install ipykernel -U --force-reinstall'" - ] - } - ], + "outputs": [], "source": [ "# Install esm and other dependencies\n", "! pip install esm\n", @@ -54,7 +43,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 2, "metadata": {}, "outputs": [], "source": [ @@ -65,7 +54,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ @@ -87,7 +76,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -138,19 +127,29 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Requesting a specific hidden layer\n", + "# Requesting hidden states for the 6B model\n", + "\n", + "ESM C 6B's hidden states are really large, so we offer two options:\n", + "\n", + "1) Request mean-pooled hidden states. This allows you to get all layers simultaneously\n", + "\n", + "2) Request one layer at a time. Refer to the model page on https://forge.evolutionaryscale.ai/ to find the number of hidden layers for each model. \n", "\n", - "ESM C 6B's hidden states are really large, so we only allow one specific layer to be requested per API call. This also works for other ESM C models, but it is required for ESM C 6B. \n", - "Refer to https://forge.evolutionaryscale.ai/console to find the number of hidden layers for each model. " + "If you for some reason can't assess which layer to choose and have to pick one blindly, the second to last hidden state is a good, safe choice. Often a layer earlier in the model will do a better job at your task. The second best blind guess is often 2/3'rds of the way through the model. The most principled way to make this choice is to write an evaluation for your task and train a classifier at each layer. The performance curve throughout the network will often give a clear indication which part of the network to use." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "# ESMC_6B_EMBEDDING_CONFIG = LogitsConfig(return_hidden_states=True, ith_hidden_layer=55)" + "# Request mean-pooled hidden states\n", + "# MEAN_POOLED_EMBEDDING_CONFIG = LogitsConfig(return_hidden_states=True, return_mean_hidden_states=True)\n", + "\n", + "# Request a single hidden layer at a time\n", + "# NUM_ESMC_6B_LAYERS = 80\n", + "# ONE_LAYER_EMBEDDING_CONFIG = LogitsConfig(return_hidden_states=True, ith_hidden_layer=NUM_ESMC_6B_LAYERS)" ] }, { @@ -164,28 +163,28 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "--2025-01-16 00:34:10-- https://docs.google.com/uc?export=download&id=1SpOkL11MJxIgy99dqufvUNJuCiuhxuyg\n", - "Resolving docs.google.com (docs.google.com)... 142.251.46.238, 2607:f8b0:4005:811::200e\n", - "Connecting to docs.google.com (docs.google.com)|142.251.46.238|:443... connected.\n", + "--2025-10-15 01:22:42-- https://docs.google.com/uc?export=download&id=1SpOkL11MJxIgy99dqufvUNJuCiuhxuyg\n", + "Resolving docs.google.com (docs.google.com)... 142.250.189.174, 2607:f8b0:4005:813::200e\n", + "Connecting to docs.google.com (docs.google.com)|142.250.189.174|:443... connected.\n", "HTTP request sent, awaiting response... 303 See Other\n", "Location: https://drive.usercontent.google.com/download?id=1SpOkL11MJxIgy99dqufvUNJuCiuhxuyg&export=download [following]\n", - "--2025-01-16 00:34:10-- https://drive.usercontent.google.com/download?id=1SpOkL11MJxIgy99dqufvUNJuCiuhxuyg&export=download\n", - "Resolving drive.usercontent.google.com (drive.usercontent.google.com)... 142.250.191.33, 2607:f8b0:4005:80f::2001\n", - "Connecting to drive.usercontent.google.com (drive.usercontent.google.com)|142.250.191.33|:443... connected.\n", + "--2025-10-15 01:22:42-- https://drive.usercontent.google.com/download?id=1SpOkL11MJxIgy99dqufvUNJuCiuhxuyg&export=download\n", + "Resolving drive.usercontent.google.com (drive.usercontent.google.com)... 142.250.191.65, 2607:f8b0:4005:810::2001\n", + "Connecting to drive.usercontent.google.com (drive.usercontent.google.com)|142.250.191.65|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: 43132 (42K) [application/octet-stream]\n", "Saving to: ‘adk.csv’\n", "\n", "adk.csv 100%[===================>] 42.12K --.-KB/s in 0.02s \n", "\n", - "2025-01-16 00:34:13 (1.93 MB/s) - ‘adk.csv’ saved [43132/43132]\n", + "2025-10-15 01:22:43 (2.49 MB/s) - ‘adk.csv’ saved [43132/43132]\n", "\n" ] } @@ -196,7 +195,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 15, "metadata": {}, "outputs": [], "source": [ @@ -212,61 +211,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 16, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Retrying... Attempt 1 after 1.0s due to: (502, 'Failure in logits: {\"status\":\"error\",\"message\":\"Model unavailable - please retry\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (502, 'Failure in logits: {\"status\":\"error\",\"message\":\"Model unavailable - please retry\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (502, 'Failure in encode: {\"status\":\"error\",\"message\":\"Model unavailable - please retry\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 3 after 4.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 3 after 4.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 3 after 4.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 3 after 4.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 52 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 52 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 54 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 54 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 52 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 52 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 54 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 54 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in logits: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 52 requests for esmc-300m-2024-12 and logits.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 54 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 54 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 51 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 51 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 51 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 51 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 51 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (502, 'Failure in logits: {\"status\":\"error\",\"message\":\"Model unavailable - please retry\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 2 after 2.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (429, 'Failure in encode: {\"status\":\"error\",\"message\":\"You have exceeded your usage cap of 50 requests during the last minute with 50 requests for esmc-300m-2024-12 and encode.\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (502, 'Failure in logits: {\"status\":\"error\",\"message\":\"Model unavailable - please retry\"}')\n", - "Retrying... Attempt 1 after 1.0s due to: (502, 'Failure in logits: {\"status\":\"error\",\"message\":\"Model unavailable - please retry\"}')Retrying... Attempt 1 after 1.0s due to: (502, 'Failure in encode: {\"status\":\"error\",\"message\":\"Model unavailable - please retry\"}')\n", - "\n", - "Retrying... Attempt 2 after 2.0s due to: (502, 'Failure in encode: {\"status\":\"error\",\"message\":\"Model unavailable - please retry\"}')\n" - ] - } - ], + "outputs": [], "source": [ "# You may see some error messages due to rate limits on each Forge account,\n", "# but this will retry until the embedding job is complete\n", @@ -276,7 +223,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 17, "metadata": {}, "outputs": [ { @@ -293,7 +240,7 @@ "# we'll summarize the embeddings using their mean across the sequence dimension\n", "# which allows us to compare embeddings for sequences of different lengths\n", "all_mean_embeddings = [\n", - " torch.mean(output.hidden_states, dim=-2).squeeze() for output in outputs\n", + " torch.mean(output.hidden_states.float(), dim=-2).squeeze() for output in outputs\n", "]\n", "\n", "# now we have a list of tensors of [num_layers, hidden_size]\n", @@ -311,7 +258,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 18, "metadata": {}, "outputs": [], "source": [ @@ -324,14 +271,16 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 19, "metadata": {}, "outputs": [], "source": [ "def plot_embeddings_at_layer(all_mean_embeddings: torch.Tensor, layer_idx: int):\n", - " stacked_mean_embeddings = torch.stack(\n", - " [embedding[layer_idx, :] for embedding in all_mean_embeddings]\n", - " ).numpy()\n", + " stacked_mean_embeddings = (\n", + " torch.stack([embedding[layer_idx, :] for embedding in all_mean_embeddings])\n", + " .float()\n", + " .numpy()\n", + " )\n", "\n", " # project all the embeddings to 2D using PCA\n", " pca = PCA(n_components=2)\n", @@ -361,12 +310,12 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 20, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", 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", + "image/png": 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"text/plain": [ "
" ] @@ -400,13 +349,21 @@ ], "metadata": { "kernelspec": { - "display_name": "default", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", "name": "python", - "version": "3.11.11" + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.9" } }, "nbformat": 4, diff --git a/esm/__init__.py b/esm/__init__.py index 3348d7f9..79e4386b 100644 --- a/esm/__init__.py +++ b/esm/__init__.py @@ -1 +1 @@ -__version__ = "3.2.3" +__version__ = "3.2.4" diff --git a/esm/sdk/api.py b/esm/sdk/api.py index de3ccb4f..77a42b0e 100644 --- a/esm/sdk/api.py +++ b/esm/sdk/api.py @@ -77,6 +77,7 @@ def from_protein_chain( sasa=protein_chain.sasa().tolist(), function_annotations=None, coordinates=torch.tensor(protein_chain.atom37_positions), + plddt=torch.tensor(protein_chain.confidence), ) else: return ESMProtein( @@ -85,6 +86,7 @@ def from_protein_chain( sasa=None, function_annotations=None, coordinates=torch.tensor(protein_chain.atom37_positions), + plddt=torch.tensor(protein_chain.confidence), ) @classmethod @@ -104,6 +106,7 @@ def from_protein_complex( coordinates=torch.tensor( protein_complex.atom37_positions, dtype=torch.float32 ), + plddt=torch.tensor(protein_complex.confidence), ) def to_pdb(self, pdb_path: PathOrBuffer) -> None: @@ -325,7 +328,9 @@ def use_generative_unmasking_strategy(self): @define class InverseFoldingConfig: invalid_ids: Sequence[int] = [] - temperature: float = 1.0 + temperature: float = 0.1 + seed: int | None = None + decode_in_residue_index_order: bool = False ## Low Level Endpoint Types diff --git a/esm/sdk/forge.py b/esm/sdk/forge.py index ea2119b3..9c65c5f1 100644 --- a/esm/sdk/forge.py +++ b/esm/sdk/forge.py @@ -119,6 +119,8 @@ def process_inverse_fold_request( inverse_folding_config = { "invalid_ids": config.invalid_ids, "temperature": config.temperature, + "seed": config.seed, + "decode_in_residue_index_order": config.decode_in_residue_index_order, } request = { "coordinates": maybe_list(coordinates, convert_nan_to_none=True), diff --git a/esm/utils/structure/molecular_complex.py b/esm/utils/structure/molecular_complex.py index 3b2ffe7e..e49be51c 100644 --- a/esm/utils/structure/molecular_complex.py +++ b/esm/utils/structure/molecular_complex.py @@ -707,8 +707,9 @@ def to_mmcif(self) -> str: atom_array.chain_id = np.array(atom_chain_ids, dtype="U4") atom_array.res_name = np.array(atom_res_names, dtype="U4") atom_array.hetero = atom_hetero - atom_array.b_factor = atom_bfactors atom_array.atom_name = np.array(atom_names, dtype="U4") + atom_array.add_annotation("b_factor", dtype=float) + atom_array.b_factor = atom_bfactors # Use existing elements or infer them from atom names if self.atom_elements is not None and len(self.atom_elements) == n_atoms: diff --git a/esm/utils/structure/protein_chain.py b/esm/utils/structure/protein_chain.py index 4889886e..2b4c8165 100644 --- a/esm/utils/structure/protein_chain.py +++ b/esm/utils/structure/protein_chain.py @@ -1121,7 +1121,9 @@ def normalize_coordinates(self) -> ProteinChain: def infer_oxygen(self) -> ProteinChain: """Oxygen position is fixed given N, CA, C atoms. 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parameterized ; extra == 'dev' - psutil ; extra == 'dev' @@ -6432,8 +6433,7 @@ packages: - dill<0.3.5 ; extra == 'dev' - evaluate>=0.2.0 ; extra == 'dev' - pytest-timeout ; extra == 'dev' - - ruff==0.5.1 ; extra == 'dev' - - sacrebleu>=1.4.12,<2.0.0 ; extra == 'dev' + - ruff==0.11.2 ; extra == 'dev' - rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1 ; extra == 'dev' - nltk<=3.8.1 ; extra == 'dev' - gitpython<3.1.19 ; extra == 'dev' @@ -6442,6 +6442,7 @@ packages: - beautifulsoup4 ; extra == 'dev' - tensorboard ; extra == 'dev' - pydantic ; extra == 'dev' + - sacrebleu>=1.4.12,<2.0.0 ; extra == 'dev' - faiss-cpu ; extra == 'dev' - cookiecutter==1.7.3 ; extra == 'dev' - isort>=5.5.4 ; extra == 'dev' @@ -6456,10 +6457,12 @@ packages: - sudachidict-core>=20220729 ; extra == 'dev' - rhoknp>=1.1.0,<1.3.1 ; extra == 'dev' - scikit-learn ; extra == 'dev' - - pytest>=7.2.0,<8.0.0 ; extra == 'dev-tensorflow' + - pytest>=7.2.0 ; extra == 'dev-tensorflow' - pytest-asyncio ; extra == 'dev-tensorflow' - pytest-rich ; extra == 'dev-tensorflow' - pytest-xdist ; extra == 'dev-tensorflow' + - pytest-order ; extra == 'dev-tensorflow' + - pytest-rerunfailures ; extra == 'dev-tensorflow' - timeout-decorator ; extra == 'dev-tensorflow' - parameterized ; extra == 'dev-tensorflow' - psutil ; extra == 'dev-tensorflow' @@ -6467,8 +6470,7 @@ packages: - dill<0.3.5 ; extra == 'dev-tensorflow' - evaluate>=0.2.0 ; extra == 'dev-tensorflow' - pytest-timeout ; extra == 'dev-tensorflow' - - ruff==0.5.1 ; extra == 'dev-tensorflow' - - sacrebleu>=1.4.12,<2.0.0 ; extra == 'dev-tensorflow' + - ruff==0.11.2 ; extra == 'dev-tensorflow' - rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1 ; extra == 'dev-tensorflow' - nltk<=3.8.1 ; extra == 'dev-tensorflow' - gitpython<3.1.19 ; extra == 'dev-tensorflow' @@ -6478,6 +6480,7 @@ packages: - tensorboard ; extra == 'dev-tensorflow' - pydantic ; extra == 'dev-tensorflow' - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'dev-tensorflow' + - sacrebleu>=1.4.12,<2.0.0 ; extra == 'dev-tensorflow' - faiss-cpu ; extra == 'dev-tensorflow' - cookiecutter==1.7.3 ; extra == 'dev-tensorflow' - tensorflow>2.9,<2.16 ; extra == 'dev-tensorflow' @@ -6499,10 +6502,12 @@ packages: - pyctcdecode>=0.4.0 ; extra == 'dev-tensorflow' - phonemizer ; extra == 'dev-tensorflow' - kenlm ; extra == 'dev-tensorflow' - - pytest>=7.2.0,<8.0.0 ; extra == 'dev-torch' + - pytest>=7.2.0 ; extra == 'dev-torch' - pytest-asyncio ; extra == 'dev-torch' - pytest-rich ; extra == 'dev-torch' - pytest-xdist ; extra == 'dev-torch' + - pytest-order ; extra == 'dev-torch' + - pytest-rerunfailures ; extra == 'dev-torch' - timeout-decorator ; extra == 'dev-torch' - parameterized ; extra == 'dev-torch' - psutil ; extra == 'dev-torch' @@ -6510,8 +6515,7 @@ packages: - dill<0.3.5 ; extra == 'dev-torch' - evaluate>=0.2.0 ; extra == 'dev-torch' - pytest-timeout ; extra == 'dev-torch' - - ruff==0.5.1 ; extra == 'dev-torch' - - sacrebleu>=1.4.12,<2.0.0 ; extra == 'dev-torch' + - ruff==0.11.2 ; extra == 'dev-torch' - rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1 ; extra == 'dev-torch' - nltk<=3.8.1 ; extra == 'dev-torch' - gitpython<3.1.19 ; extra == 'dev-torch' @@ -6521,9 +6525,10 @@ packages: - tensorboard ; extra == 'dev-torch' - pydantic ; extra == 'dev-torch' - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'dev-torch' + - sacrebleu>=1.4.12,<2.0.0 ; extra == 'dev-torch' - faiss-cpu ; extra == 'dev-torch' - cookiecutter==1.7.3 ; extra == 'dev-torch' - - torch>=2.0 ; extra == 'dev-torch' + - torch>=2.1,<2.7 ; extra == 'dev-torch' - accelerate>=0.26.0 ; extra == 'dev-torch' - protobuf ; extra == 'dev-torch' - tokenizers>=0.21,<0.22 ; extra == 'dev-torch' @@ -6533,6 +6538,7 @@ packages: - phonemizer ; extra == 'dev-torch' - kenlm ; extra == 'dev-torch' - pillow>=10.0.1,<=15.0 ; extra == 'dev-torch' + - kernels>=0.4.4,<0.5 ; extra == 'dev-torch' - optuna ; extra == 'dev-torch' - ray[tune]>=2.7.0 ; extra == 'dev-torch' - sigopt ; extra == 'dev-torch' @@ -6553,6 +6559,7 @@ packages: - scikit-learn ; extra == 'dev-torch' - onnxruntime>=1.4.0 ; extra == 'dev-torch' - onnxruntime-tools>=1.4.2 ; extra == 'dev-torch' + - num2words ; extra == 'dev-torch' - jax>=0.4.1,<=0.4.13 ; extra == 'flax' - jaxlib>=0.4.1,<=0.4.13 ; extra == 'flax' - flax>=0.4.1,<=0.7.0 ; extra == 'flax' @@ -6563,6 +6570,9 @@ packages: - phonemizer ; extra == 'flax-speech' - kenlm ; extra == 'flax-speech' - ftfy ; extra == 'ftfy' + - hf-xet ; extra == 'hf-xet' + - kernels>=0.4.4,<0.5 ; extra == 'hub-kernels' + - kernels>=0.4.4,<0.5 ; extra == 'integrations' - optuna ; extra == 'integrations' - ray[tune]>=2.7.0 ; extra == 'integrations' - sigopt ; extra == 'integrations' @@ -6575,6 +6585,7 @@ packages: - rhoknp>=1.1.0,<1.3.1 ; extra == 'ja' - cookiecutter==1.7.3 ; extra == 'modelcreation' - natten>=0.14.6,<0.15.0 ; extra == 'natten' + - num2words ; extra == 'num2words' - onnxconverter-common ; extra == 'onnx' - tf2onnx ; extra == 'onnx' - onnxruntime>=1.4.0 ; extra == 'onnx' @@ -6584,7 +6595,7 @@ packages: - optuna ; extra == 'optuna' - datasets!=2.5.0 ; extra == 'quality' - isort>=5.5.4 ; extra == 'quality' - - ruff==0.5.1 ; extra == 'quality' + - ruff==0.11.2 ; extra == 'quality' - gitpython<3.1.19 ; extra == 'quality' - urllib3<2.0.0 ; extra == 'quality' - libcst ; extra == 'quality' @@ -6592,7 +6603,7 @@ packages: - ray[tune]>=2.7.0 ; extra == 'ray' - faiss-cpu ; extra == 'retrieval' - datasets!=2.5.0 ; extra == 'retrieval' - - ruff==0.5.1 ; extra == 'ruff' + - ruff==0.11.2 ; extra == 'ruff' - sagemaker>=2.31.0 ; extra == 'sagemaker' - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'sentencepiece' - protobuf ; extra == 'sentencepiece' @@ -6607,10 +6618,12 @@ packages: - pyctcdecode>=0.4.0 ; extra == 'speech' - phonemizer ; extra == 'speech' - kenlm ; extra == 'speech' - - pytest>=7.2.0,<8.0.0 ; extra == 'testing' + - pytest>=7.2.0 ; extra == 'testing' - pytest-asyncio ; extra == 'testing' - pytest-rich ; extra == 'testing' - pytest-xdist ; extra == 'testing' + - pytest-order ; extra == 'testing' + - pytest-rerunfailures ; extra == 'testing' - timeout-decorator ; extra == 'testing' - parameterized ; extra == 'testing' - psutil ; extra == 'testing' @@ -6618,8 +6631,7 @@ packages: - dill<0.3.5 ; extra == 'testing' - evaluate>=0.2.0 ; extra == 'testing' - pytest-timeout ; extra == 'testing' - - ruff==0.5.1 ; extra == 'testing' - - sacrebleu>=1.4.12,<2.0.0 ; extra == 'testing' + - ruff==0.11.2 ; extra == 'testing' - rouge-score!=0.0.7,!=0.0.8,!=0.1,!=0.1.1 ; extra == 'testing' - nltk<=3.8.1 ; extra == 'testing' - gitpython<3.1.19 ; extra == 'testing' @@ -6629,6 +6641,7 @@ packages: - tensorboard ; extra == 'testing' - pydantic ; extra == 'testing' - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'testing' + - sacrebleu>=1.4.12,<2.0.0 ; extra == 'testing' - faiss-cpu ; extra == 'testing' - cookiecutter==1.7.3 ; extra == 'testing' - tensorflow>2.9,<2.16 ; extra == 'tf' @@ -6651,7 +6664,7 @@ packages: - blobfile ; extra == 'tiktoken' - timm<=1.0.11 ; extra == 'timm' - tokenizers>=0.21,<0.22 ; extra == 'tokenizers' - - torch>=2.0 ; extra == 'torch' + - torch>=2.1,<2.7 ; extra == 'torch' - accelerate>=0.26.0 ; extra == 'torch' - torchaudio ; extra == 'torch-speech' - librosa ; extra == 'torch-speech' @@ -6661,7 +6674,7 @@ packages: - torchvision ; extra == 'torch-vision' - pillow>=10.0.1,<=15.0 ; extra == 'torch-vision' - filelock ; extra == 'torchhub' - - huggingface-hub>=0.24.0,<1.0 ; extra == 'torchhub' + - huggingface-hub>=0.30.0,<1.0 ; extra == 'torchhub' - importlib-metadata ; extra == 'torchhub' - numpy>=1.17 ; extra == 'torchhub' - packaging>=20.0 ; extra == 'torchhub' @@ -6669,10 +6682,10 @@ packages: - regex!=2019.12.17 ; extra == 'torchhub' - requests ; extra == 'torchhub' - sentencepiece>=0.1.91,!=0.1.92 ; extra == 'torchhub' - - torch>=2.0 ; extra == 'torchhub' + - torch>=2.1,<2.7 ; extra == 'torchhub' - tokenizers>=0.21,<0.22 ; extra == 'torchhub' - tqdm>=4.27 ; extra == 'torchhub' - - av==9.2.0 ; extra == 'video' + - av ; extra == 'video' - pillow>=10.0.1,<=15.0 ; extra == 'vision' requires_python: '>=3.9.0' - pypi: https://files.pythonhosted.org/packages/06/00/59500052cb1cf8cf5316be93598946bc451f14072c6ff256904428eaf03c/triton-3.2.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl diff --git a/pyproject.toml b/pyproject.toml index 923d306e..e4ce17b2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "esm" -version = "3.2.3" +version = "3.2.4" description = "EvolutionaryScale open model repository" readme = "README.md" requires-python = ">=3.12,<3.13" @@ -24,7 +24,7 @@ dependencies = [ "torch>=2.2.0", "torchvision", "torchtext", - "transformers<4.48.2", + "transformers==4.52.4", "ipython", "einops", "biotite>=1.0.0", diff --git a/tests/Makefile b/tests/Makefile index 5af442ea..61c37238 100644 --- a/tests/Makefile +++ b/tests/Makefile @@ -3,7 +3,11 @@ DOCKER_TAG ?= dev DOCKER_IMAGE_OSS=oss_pytests:${DOCKER_TAG} build-oss-ci: - docker build -f oss_pytests/Dockerfile oss_pytests -t $(DOCKER_IMAGE_OSS) + docker build \ + --output=type=docker \ + -f oss_pytests/Dockerfile \ + -t $(DOCKER_IMAGE_OSS) \ + oss_pytests start-docker-oss: docker run \ From 87e3bf28a4c92e08f621b188366ace7f5b4ed247 Mon Sep 17 00:00:00 2001 From: Ishaan Mathur Date: Wed, 22 Oct 2025 14:28:24 +0000 Subject: [PATCH 2/4] infer oxygen in protein complex --- esm/utils/structure/protein_complex.py | 4 +++- 1 file changed, 3 insertions(+), 1 deletion(-) diff --git a/esm/utils/structure/protein_complex.py b/esm/utils/structure/protein_complex.py index 306c8832..0ef2465a 100644 --- a/esm/utils/structure/protein_complex.py +++ b/esm/utils/structure/protein_complex.py @@ -562,7 +562,9 @@ def join_arrays(arrays: Sequence[np.ndarray], sep: np.ndarray): def infer_oxygen(self) -> ProteinComplex: """Oxygen position is fixed given N, CA, C atoms. Infer it if not provided.""" - O_missing_indices = np.argwhere(np.isnan(self.atoms["O"]).any(axis=1)).squeeze() + O_missing_indices = np.argwhere( + ~np.isfinite(self.atoms["O"]).all(axis=1) + ).squeeze() O_vector = torch.tensor([0.6240, -1.0613, 0.0103], dtype=torch.float32) N, CA, C = torch.from_numpy(self.atoms[["N", "CA", "C"]]).float().unbind(dim=1) From e3220489fdfe8a04fc00038902b01af9e51cfa59 Mon Sep 17 00:00:00 2001 From: Ishaan Mathur Date: Wed, 22 Oct 2025 16:10:24 +0000 Subject: [PATCH 3/4] updating version --- esm/__init__.py | 2 +- pixi.lock | 65 +++++++++++++++++++++++++++++++++++++++++++++++-- pyproject.toml | 2 +- 3 files changed, 65 insertions(+), 4 deletions(-) diff --git a/esm/__init__.py b/esm/__init__.py index 79e4386b..3dc1ccb5 100644 --- a/esm/__init__.py +++ b/esm/__init__.py @@ -1 +1 @@ -__version__ = "3.2.4" +__version__ = "3.2.4.a0" diff --git a/pixi.lock b/pixi.lock index 5af4fec9..33af06cd 100644 --- a/pixi.lock +++ b/pixi.lock @@ -10,6 +10,7 @@ environments: - 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