From c6b8c342aa99c823cd63ff11e0047ccd2f962117 Mon Sep 17 00:00:00 2001 From: Chetan Mishra Date: Wed, 5 Mar 2025 15:08:52 -0500 Subject: [PATCH] ported over updates from internal (#208) Co-authored-by: chetan --- .gitignore | 5 +- cookbook/snippets/esmc.py | 33 +- cookbook/tutorials/3_gfp_design.ipynb | 25 +- esm/__init__.py | 2 +- esm/sdk/api.py | 9 +- esm/sdk/forge.py | 48 + esm/sdk/sagemaker.py | 4 +- esm/tokenization/sequence_tokenizer.py | 47 +- esm/tokenization/tokenizer_base.py | 41 +- esm/utils/generation_test.py | 2 + pixi.lock | 2207 ++++++++++++++++++++++++ pyproject.toml | 13 +- tools/generate.ipynb | 9 +- 13 files changed, 2392 insertions(+), 53 deletions(-) create mode 100644 pixi.lock diff --git a/.gitignore b/.gitignore index de06c1a..9e83a30 100644 --- a/.gitignore +++ b/.gitignore @@ -1 +1,4 @@ -esm.egg-info \ No newline at end of file +esm.egg-info +# pixi environments +.pixi +*.egg-info diff --git a/cookbook/snippets/esmc.py b/cookbook/snippets/esmc.py index ce189d9..335f3e1 100644 --- a/cookbook/snippets/esmc.py +++ b/cookbook/snippets/esmc.py @@ -1,13 +1,18 @@ +import os + from esm.models.esmc import ESMC +from esm.sdk import client from esm.sdk.api import ( ESMCInferenceClient, ESMProtein, + ESMProteinTensor, LogitsConfig, LogitsOutput, ) +from esm.sdk.forge import ESM3ForgeInferenceClient -def main(client: ESMCInferenceClient): +def main(client: ESMCInferenceClient | ESM3ForgeInferenceClient): # ================================================================ # Example usage: one single protein # ================================================================ @@ -15,13 +20,16 @@ def main(client: ESMCInferenceClient): # Use logits endpoint. Using bf16 for inference optimization protein_tensor = client.encode(protein) + assert isinstance( + protein_tensor, ESMProteinTensor + ), f"Expected ESMProteinTensor but got error: {protein_tensor}" output = client.logits( protein_tensor, LogitsConfig(sequence=True, return_embeddings=True, return_hidden_states=True), ) assert isinstance( output, LogitsOutput - ), f"LogitsOutput was expected but got {output}" + ), f"LogitsOutput was expected but got error: {output}" assert output.logits is not None and output.logits.sequence is not None assert output.embeddings is not None assert output.hidden_states is not None @@ -30,9 +38,15 @@ def main(client: ESMCInferenceClient): ) # request a specific hidden layer. + assert isinstance( + protein_tensor, ESMProteinTensor + ), f"Expected ESMProteinTensor but got error: {protein_tensor}" output = client.logits( protein_tensor, LogitsConfig(return_hidden_states=True, ith_hidden_layer=1) ) + assert isinstance( + output, LogitsOutput + ), f"LogitsOutput was expected but got error: {output}" assert output.hidden_states is not None print(f"Client returned hidden states with shape {output.hidden_states.shape}") @@ -57,6 +71,15 @@ def raw_forward(model: ESMC): if __name__ == "__main__": - model = ESMC.from_pretrained("esmc_300m") - main(model) - raw_forward(model) + if os.environ.get("ESM_API_KEY", ""): + print("ESM_API_KEY found. Trying to use model from Forge...") + main(client(model="esmc-300m-2024-12")) + else: + print("No ESM_API_KEY found. Trying to load model locally...") + print( + "TO try this script with a Forge API, please run ESM_API_KEY=your_api_key python esm3.py" + ) + main(ESMC.from_pretrained("esm3_sm_open_v1")) + model = ESMC.from_pretrained("esmc_300m") + main(model) + raw_forward(model) diff --git a/cookbook/tutorials/3_gfp_design.ipynb b/cookbook/tutorials/3_gfp_design.ipynb index f4e56cf..2d548be 100644 --- a/cookbook/tutorials/3_gfp_design.ipynb +++ b/cookbook/tutorials/3_gfp_design.ipynb @@ -50,7 +50,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 13, "metadata": { "id": "poK5NTaXRGcX" }, @@ -85,7 +85,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 14, "metadata": { "id": "zNrU9Q2SYonX" }, @@ -105,7 +105,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 26, "metadata": { "id": "Tna_mjGOjdXA" }, @@ -367,7 +367,8 @@ "source": [ "%%time\n", "\n", - "num_tokens_to_decode = (prompt.sequence == 32).sum().item()\n", + "# Based on internal, there's not a benefit to iterative decoding past 20 steps\n", + "num_tokens_to_decode = min((prompt.sequence == 32).sum().item(), 20)\n", "\n", "sequence_generation = model.generate(\n", " # Generate a sequence.\n", @@ -380,7 +381,7 @@ "length_of_sequence = sequence_generation.sequence.numel() - 2\n", "sequence_generation = model.generate(\n", " sequence_generation,\n", - " GenerationConfig(track=\"structure\", num_steps=length_of_sequence, temperature=0.0),\n", + " GenerationConfig(track=\"structure\", num_steps=1, temperature=0.0),\n", ")\n", "\n", "# Decode to AA string and coordinates.\n", @@ -528,11 +529,21 @@ "provenance": [] }, "kernelspec": { - "display_name": "Python 3", + "display_name": "default", + "language": "python", "name": "python3" }, "language_info": { - "name": "python" + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.0" } }, "nbformat": 4, diff --git a/esm/__init__.py b/esm/__init__.py index 0e6bc5d..871d660 100644 --- a/esm/__init__.py +++ b/esm/__init__.py @@ -1,2 +1,2 @@ -__version__ = "3.1.4" +__version__ = "3.1.5" diff --git a/esm/sdk/api.py b/esm/sdk/api.py index 8d67038..759fd47 100644 --- a/esm/sdk/api.py +++ b/esm/sdk/api.py @@ -266,7 +266,8 @@ class ESMProteinError(Exception, ProteinType): @define class GenerationConfig: track: str = "" - invalid_ids: Sequence[int] = [] + # By default avoid sampling the amino acid "X" + invalid_ids: Sequence[int] = [24] # Controls the number of tokens to unmask during each round of iterative generation. schedule: str = attr.field( validator=attr.validators.in_(["cosine", "linear"]), default="cosine" @@ -275,11 +276,11 @@ class GenerationConfig: # "random" will unmask a correct number of tokens randomly. # "entropy" will unmask the tokens with the lowest logit entropy first. strategy: str = attr.field( - validator=attr.validators.in_(["random", "entropy"]), default="entropy" + validator=attr.validators.in_(["random", "entropy"]), default="random" ) - # Set this to a higher value for better generation results. + # Setting default to 20, as there is diminishing return for decoding steps more than 20. # Note that this needs to be less than or equal to the sequence length. - num_steps: int = 1 + num_steps: int = 20 temperature: float = 1.0 temperature_annealing: bool = False top_p: float = 1.0 diff --git a/esm/sdk/forge.py b/esm/sdk/forge.py index 25dadbd..415719d 100644 --- a/esm/sdk/forge.py +++ b/esm/sdk/forge.py @@ -60,6 +60,10 @@ def log_retry_attempt(retry_state): def _validate_protein_tensor_input(input): + if isinstance(input, ESMProteinError): + raise ValueError( + f"Input must be an ESMProteinTensor instance, but received an ESMProteinError instead: {input.error_code} {input.error_msg}" + ) if not isinstance(input, ESMProteinTensor): raise ValueError( f"Input must be an ESMProteinTensor instance, but received {type(input)} instead. " @@ -71,14 +75,25 @@ class SequenceStructureForgeInferenceClient: def __init__( self, url: str = "https://forge.evolutionaryscale.ai", + model: str | None = None, token: str = "", request_timeout: int | None = None, ): + """ + Forge client for folding and inverse folding between sequence and structure spaces. + + Args: + url: URL of the Forge server. + model: Name of the model to be used for folding / inv folding. + token: API token. + request_timeout: Override the system default request timeout, in seconds. + """ if token == "": raise RuntimeError( "Please provide a token to connect to Forge via token=YOUR_API_TOKEN_HERE" ) self.url = url + self.model = model self.token = token self.headers = {"Authorization": f"Bearer {self.token}"} self.request_timeout = request_timeout @@ -89,9 +104,19 @@ class SequenceStructureForgeInferenceClient: potential_sequence_of_concern: bool, model_name: str | None = None, ) -> ESMProtein | ESMProteinError: + """Predict coordinates for a protein sequence. + + Args: + sequence: Protein sequence to be folded. + potential_sequence_of_concern: Self disclosed potential_of_concern bit. + This bit is largely ignored by the fold() endpoint. + model_name: Override the client level model name if needed. + """ request = {"sequence": sequence} if model_name is not None: request["model"] = model_name + elif self.model is not None: + request["model"] = self.model try: data = self._post("fold", request, potential_sequence_of_concern) except ESMProteinError as e: @@ -109,6 +134,17 @@ class SequenceStructureForgeInferenceClient: potential_sequence_of_concern: bool, model_name: str | None = None, ) -> ESMProtein | ESMProteinError: + """Generate protein sequence from its structure. + + This endpoint is only supported by generative models like ESM3. + + Args: + coordinates: Protein sequence coordinates to be inversely folded. + config: Configurations related to inverse folding generation. + potential_sequence_of_concern: Self disclosed potential_of_concern bit. + Requires special permission to use. + model_name: Override the client level model name if needed. + """ inverse_folding_config = { "invalid_ids": config.invalid_ids, "temperature": config.temperature, @@ -119,6 +155,8 @@ class SequenceStructureForgeInferenceClient: } if model_name is not None: request["model"] = model_name + elif self.model is not None: + request["model"] = self.model try: data = self._post("inverse_fold", request, potential_sequence_of_concern) except ESMProteinError as e: @@ -208,6 +246,16 @@ class ESM3ForgeInferenceClient(ESM3InferenceClient): @retry_decorator def generate(self, input: ProteinType, config: GenerationConfig) -> ProteinType: + if isinstance(input, ESMProteinError): + raise ValueError( + f"Input must be an ESMProtein or ESMProteinTensor instance, but received an ESMProteinError instead: {input.error_code} {input.error_msg}" + ) + assert isinstance(input, ESMProtein) or isinstance(input, ESMProteinTensor) + if input.sequence is not None and config.num_steps > len(input.sequence): + config.num_steps = len(input.sequence) + print( + "Warning: num_steps cannot exceed sequence length. Setting num_steps to sequence length." + ) if isinstance(input, ESMProtein): output = self.__generate_protein(input, config) elif isinstance(input, ESMProteinTensor): diff --git a/esm/sdk/sagemaker.py b/esm/sdk/sagemaker.py index d239311..d6eda85 100644 --- a/esm/sdk/sagemaker.py +++ b/esm/sdk/sagemaker.py @@ -9,14 +9,14 @@ from esm.sdk.forge import ( class SequenceStructureSageMakerClient(SequenceStructureForgeInferenceClient): - def __init__(self, endpoint_name: str): + def __init__(self, endpoint_name: str, model: str | None = None): """SequenceStructure (folding and inverse folding) client that talks to a SageMaker endpoint. Args: endpoint_name: Name of the SageMaker endpoint. """ # Dummy URL and token to make SequenceStructureForgeInferenceClient happy. - super().__init__(url="", token="dummy") + super().__init__(url="", model=model, token="dummy") self._endpoint_name = endpoint_name diff --git a/esm/tokenization/sequence_tokenizer.py b/esm/tokenization/sequence_tokenizer.py index a56ae74..2df0d44 100644 --- a/esm/tokenization/sequence_tokenizer.py +++ b/esm/tokenization/sequence_tokenizer.py @@ -72,13 +72,45 @@ class EsmSequenceTokenizer(PreTrainedTokenizerFast, EsmTokenizerBase): def bos_token_id(self): return self.cls_token_id + @property + def cls_token(self): + return self._get_token("cls_token") + + @property + def cls_token_id(self): + return self._get_token_id(self.cls_token) + + @property + def eos_token(self): + return self._get_token("eos_token") + + @property + def eos_token_id(self): + return self._get_token_id(self.eos_token) + + @property + def mask_token(self): + return self._get_token("mask_token") + + @property + def mask_token_id(self): + return self._get_token_id(self.mask_token) + + @property + def pad_token(self): + return self._get_token("pad_token") + + @property + def pad_token_id(self): + return self._get_token_id(self.pad_token) + @property def chain_break_token(self): return self.cb_token @property def chain_break_token_id(self): - return self.convert_tokens_to_ids(self.chain_break_token) + return self._get_token_id(self.chain_break_token) @property def all_token_ids(self): @@ -87,3 +119,16 @@ class EsmSequenceTokenizer(PreTrainedTokenizerFast, EsmTokenizerBase): @property def special_token_ids(self): return self.all_special_ids + + def _get_token_id(self, token) -> int: + token_id = self.convert_tokens_to_ids(token) + assert isinstance(token_id, int) + return token_id + + def _get_token(self, token_name: str) -> str: + # NOTE: Tokenizers library overloads __getattr__ to expose special tokens + # Adding a helper method around it keeps the base class functionality without overriding + # the property. See: https://github.com/huggingface/transformers/blob/41925e42135257361b7f02aa20e3bbdab3f7b923/src/transformers/tokenization_utils_base.py#L1086 + token_str = self.__getattr__(token_name) + assert isinstance(token_str, str) + return token_str diff --git a/esm/tokenization/tokenizer_base.py b/esm/tokenization/tokenizer_base.py index 4358ab5..5425a1b 100644 --- a/esm/tokenization/tokenizer_base.py +++ b/esm/tokenization/tokenizer_base.py @@ -3,40 +3,21 @@ from typing import Protocol, runtime_checkable @runtime_checkable class EsmTokenizerBase(Protocol): + mask_token: str + mask_token_id: int + bos_token: str + bos_token_id: int + eos_token: str + eos_token_id: int + pad_token: str + pad_token_id: int + chain_break_token: str + chain_break_token_id: int + def encode(self, *args, **kwargs): ... def decode(self, *args, **kwargs): ... - @property - def mask_token(self) -> str: ... - - @property - def mask_token_id(self) -> int: ... - - @property - def bos_token(self) -> str: ... - - @property - def bos_token_id(self) -> int: ... - - @property - def eos_token(self) -> str: ... - - @property - def eos_token_id(self) -> int: ... - - @property - def pad_token(self) -> str: ... - - @property - def pad_token_id(self) -> int: ... - - @property - def chain_break_token(self) -> str: ... - - @property - def chain_break_token_id(self) -> int: ... - @property def all_token_ids(self): ... diff --git a/esm/utils/generation_test.py b/esm/utils/generation_test.py index a8e8c21..d7ea69e 100644 --- a/esm/utils/generation_test.py +++ b/esm/utils/generation_test.py @@ -1,6 +1,7 @@ import pytest import torch +from evolutionaryscale.models.esm3v2 import Esm3v2 from esm.sdk.api import ( ESMProtein, ESMProteinTensor, @@ -18,6 +19,7 @@ def esm3_remote_inference_client(): model = _load_esm_model( ModelName.ESM3_TINY_DEV, distributed_model=False, load_function_decoder=False ) + assert isinstance(model, Esm3v2) client = ESM3RemoteModelInferenceClient( model, tokenizers=model.tokenizers, diff --git a/pixi.lock b/pixi.lock new file mode 100644 index 0000000..c869a7a --- /dev/null +++ b/pixi.lock @@ -0,0 +1,2207 @@ +version: 6 +environments: + default: + channels: + - 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"display_name": "Python 3 (ipykernel)", + "display_name": "default", "language": "python", "name": "python3" },