feat(jax): freeze to StableXLO & DeepEval #4256
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Signed-off-by: Jinzhe Zeng <[email protected]>
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Actionable comments posted: 7
🧹 Outside diff range and nitpick comments (10)
deepmd/dpmodel/utils/serialization.py (1)
144-144: Consider using consistent data structures for extension checks.While the implementation is correct, there's an inconsistency in the data structures used for extension checking:
save_dp_modeluses tuple:in (".dp", ".hlo")load_dp_modeluses set:in {".dp", ".hlo"}For consistency and maintainability, consider using the same data structure in both functions.
Suggested change:
- if filename_extension in {".dp", ".hlo"}: + if filename_extension in (".dp", ".hlo"):Or alternatively, if you prefer sets for performance:
# In save_dp_model: - if filename_extension in (".dp", ".hlo"): + if filename_extension in {".dp", ".hlo"}:source/tests/consistent/io/test_io.py (1)
135-135: Consider adjusting numerical tolerances for cross-backend comparison.The test now includes the JAX backend in cross-backend result verification. However, the current tolerances (rtol=1e-12, atol=1e-12) might be too strict for comparing results across different backends, especially when comparing with JAX which might use different numerical implementations.
Consider using more relaxed tolerances (e.g., rtol=1e-7, atol=1e-10) to account for minor numerical differences between backends while still ensuring correctness.
deepmd/jax/utils/serialization.py (1)
70-85: Consider deep copying the data dictionary to prevent unintended mutationsUsing
data.copy()creates a shallow copy, which might lead to unintended side effects if the nested objects are modified elsewhere. Consider usingcopy.deepcopy(data)for a deep copy to avoid potential issues with shared references.Apply this change if deep copying is necessary:
- data = data.copy() + import copy + data = copy.deepcopy(data)deepmd/jax/model/hlo.py (7)
2-5: Standardize import statement formattingThere are inconsistent blank lines within the grouped import statements. For better readability and adherence to PEP 8 guidelines, remove unnecessary blank lines between imported items and before the closing parenthesis.
Apply the following diff to standardize the import formatting:
from typing import ( Any, - Optional, - ) from deepmd.dpmodel.model.transform_output import ( communicate_extended_output, - ) from deepmd.dpmodel.output_def import ( FittingOutputDef, ModelOutputDef, OutputVariableDef, - ) from deepmd.dpmodel.utils.nlist import ( build_neighbor_list, extend_coord_with_ghosts, - ) from deepmd.dpmodel.utils.region import ( normalize_coord, - ) from deepmd.jax.env import ( jax_export, jnp, - ) from deepmd.jax.model.base_model import ( BaseModel, - ) from deepmd.utils.data_system import ( DeepmdDataSystem, - )Also applies to: 7-9, 10-14, 15-18, 19-21, 22-25, 26-28, 29-31
52-66: Add docstring to the__init__methodThe
__init__method lacks a docstring. Adding a docstring that describes the purpose of the constructor, its parameters, and any important details will enhance code readability and maintainability.
152-153: Avoid unnecessary variable reassignmentReassigning variables
coord,box,fparam, andaparamto abbreviated names (cc,bb,fp,ap) and deleting the originals may reduce code readability. Consider using the original variable names throughout the method to maintain clarity.Apply this diff to retain the original variable names:
nframes, nloc = atype.shape[:2] -cc, bb, fp, ap = coord, box, fparam, aparam -del coord, box, fparam, aparam +coord, box, fparam, aparam = coord, box, fparam, aparam
190-194: Add docstring to themodel_output_defmethodThe
model_output_defmethod lacks a docstring. Providing a docstring will help others understand the purpose and usage of this method.
195-214: Add docstring to thecall_lowermethodThe
call_lowermethod is a key component of the class but lacks a docstring. Adding a docstring with details about the method's functionality, parameters, and return values will improve code comprehension.
215-344: Ensure all public methods have docstringsSeveral public methods, such as
get_type_map,get_rcut,get_dim_fparam,mixed_types, and others, lack docstrings. Providing docstrings for these methods enhances code readability and maintainability.
251-275: Implement serialization and model-building methods or clarify their purposeThe methods
serialize,deserialize,update_sel, andget_modelcurrently raiseNotImplementedError. If these methods are intended to be implemented later, consider adding a comment to indicate this. If they are not applicable for this class, provide an explanation or remove them to avoid confusion.Would you like assistance in implementing these methods or creating placeholders with appropriate comments?
Also applies to: 300-344
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📒 Files selected for processing (9)
- deepmd/backend/jax.py (2 hunks)
- deepmd/dpmodel/descriptor/se_e2_a.py (1 hunks)
- deepmd/dpmodel/utils/serialization.py (2 hunks)
- deepmd/jax/env.py (1 hunks)
- deepmd/jax/infer/init.py (1 hunks)
- deepmd/jax/infer/deep_eval.py (1 hunks)
- deepmd/jax/model/hlo.py (1 hunks)
- deepmd/jax/utils/serialization.py (3 hunks)
- source/tests/consistent/io/test_io.py (2 hunks)
✅ Files skipped from review due to trivial changes (2)
- deepmd/jax/env.py
- deepmd/jax/infer/init.py
🧰 Additional context used
🪛 Ruff
deepmd/jax/infer/deep_eval.py
303-306: Use ternary operator
natoms = len(atom_types[0]) if mixed_type else len(atom_types)instead ofif-else-blockReplace
if-else-block withnatoms = len(atom_types[0]) if mixed_type else len(atom_types)(SIM108)
332-335: Use ternary operator
box_input = cells.reshape([-1, 3, 3]) if cells is not None else Noneinstead ofif-else-blockReplace
if-else-block withbox_input = cells.reshape([-1, 3, 3]) if cells is not None else None(SIM108)
🔇 Additional comments (11)
deepmd/backend/jax.py (2)
74-78: Verify DeepEval implementation completeness.The implementation now returns the
DeepEvalclass, but we should verify that this class properly implements the required interface.Let's check the implementation of DeepEval:
#!/bin/bash # Description: Verify DeepEval implementation # Test 1: Check if DeepEval implements all required methods ast-grep --pattern 'class DeepEval: $$$ ' # Test 2: Check if there are any TODO/FIXME comments in the implementation rg -g '!*.pyc' -g '!*.so' -A 3 'TODO|FIXME' deepmd/jax/infer/deep_eval.py
41-41: Consider the order of file suffixes.The order of suffixes might affect file type resolution. Consider documenting whether
.hloor.jaxtakes precedence, or if the order matters for your use case.Let's check if there's any documentation or tests that specify the precedence:
✅ Verification successful
Based on the search results, I can now provide a definitive response:
The suffix order is intentionally designed for file type resolution.
The order of suffixes
[".hlo", ".jax"]is deliberate and correct. From the codebase:
.hlofiles are HDF5-based files (using h5py) that store model data in a specific format for XLA/JAX optimization.jaxfiles are directory-based checkpoints with a different storage mechanism- The serialization logic in
deepmd/jax/utils/serialization.pyhandles each format distinctly with clear precedence:
.jaxfiles use Checkpointer with composite handlers.hlofiles use HDF5 storage with specific attributesThe current order ensures proper file type resolution without conflicts.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for documentation about file suffix precedence # Test: Look for any mentions of .hlo or .jax in docs and tests rg -g '!*.pyc' -g '!*.so' -A 3 '[.](hlo|jax)' docs/ tests/Length of output: 121
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#!/bin/bash # Let's check how these suffixes are used in the codebase rg -g '!*.pyc' -g '!*.so' "suffixes.*(\\.hlo|\\.jax)" -A 3 # Also check for any file handling or extension processing logic ast-grep --pattern 'def $_(self, $$$): $$$ suffixes $$$' # Look for actual usage of these file types rg -g '!*.pyc' -g '!*.so' "\\.hlo|\\.jax" -B 2 -A 2 # Check if there are any tests related to file handling fd "test.*\\.py$" tests/ --exec grep -l "suffixes\\|[.]hlo\\|[.]jax" {}Length of output: 19333
deepmd/dpmodel/utils/serialization.py (1)
93-93: LGTM! Verify consistent handling of .hlo files.The addition of .hlo extension support is implemented correctly, maintaining the same robust HDF5-based serialization as .dp files.
Let's verify the consistent handling of both extensions:
✅ Verification successful
Based on the search results, I can now generate the final response:
Verified: .hlo files are handled consistently with .dp files
The codebase shows consistent handling of both extensions:
- Both serialization and deserialization in
dpmodel/utils/serialization.pytreat .hlo files identically to .dp files using HDF5- The JAX backend properly declares .hlo support in its supported suffixes
- Additional .hlo-specific handling exists in JAX utils for model deserialization, maintaining format compatibility
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that .hlo files are handled consistently with .dp files # throughout the codebase # Test 1: Check for any special handling of .hlo files that might differ from .dp rg -g '!*.md' -g '!*.txt' '\.hlo' -C 3 # Test 2: Verify that both extensions are always handled together rg -g '!*.md' -g '!*.txt' '\.dp.*\.hlo|\.hlo.*\.dp' -C 3Length of output: 4067
source/tests/consistent/io/test_io.py (1)
71-84: Verify suffix indices for each backend.The changes look good and make the suffix index more explicit. However, all backends are using suffix_idx=0. Please verify if this is intentional, especially for the JAX backend which might support multiple suffixes (.jax, .hlo).
✅ Verification successful
From the search results, I can see the backend suffix definitions:
- TensorFlow backend:
.pb- PyTorch backend:
.pth,.pt- JAX backend:
.hlo,.jax- DPModel backend:
.dp,.yaml,.ymlSince JAX backend has two suffixes (
.hloand.jax), and it's using index 0 in the test code, let's verify which suffix is at index 0:
Now I have enough information to provide the final response. The JAX backend defines its suffixes as
[".hlo", ".jax"], where.hlois at index 0. Therefore, usingsuffix_idx=0in the test is correct as it will use the.hlosuffix, which is the intended behavior.Using suffix_idx=0 for JAX backend is correct
The test is correctly using suffix_idx=0 for all backends, including JAX. For JAX backend, this will use the
.hlosuffix which is the first suffix in its list[".hlo", ".jax"]. This is consistent with the backend's implementation and its serialization logic.🏁 Scripts executed
The following scripts were executed for the analysis:
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#!/bin/bash # Description: Check available suffixes for each backend # Expected: Verify if using index 0 is appropriate for all backends # Search for suffix definitions in backend files echo "Checking backend suffixes:" rg -A 2 "suffixes\s*=\s*\[" --type pyLength of output: 102
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#!/bin/bash # Let's try different approaches to find backend suffix definitions # Search for Backend class definitions and their context echo "Searching for Backend classes and their properties:" rg -B 2 -A 10 "class \w+Backend\(" --type py # Search specifically for suffix-related code echo -e "\nSearching for suffix-related code:" rg "suffix" --type py # Look for backend-specific files echo -e "\nListing potential backend files:" fd -e py backendLength of output: 95223
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#!/bin/bash # Check JAX backend implementation echo "Checking JAX backend implementation:" rg -A 5 "class JAXBackend" deepmd/backend/jax.pyLength of output: 287
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#!/bin/bash # Let's get the full JAX backend class definition to see the suffixes order echo "Full JAX backend class definition:" rg -B 2 -A 15 "suffixes.*=.*\[" deepmd/backend/jax.py # Also check if there's any specific handling of JAX suffixes in the codebase echo -e "\nChecking JAX suffix usage:" rg "\.jax|\.hlo" --type pyLength of output: 6559
deepmd/dpmodel/descriptor/se_e2_a.py (2)
558-558: LGTM: Efficient use of pre-computed valuesThe change to use
self.sel_cumsumdirectly instead of recomputing the cumulative sum is a good optimization that maintains the same functionality while reducing redundant computations.
Line range hint
580-600: Verify mathematical equivalence of the new computation methodThe replacement of
einsumoperations with directsumoperations appears to maintain the same mathematical operations but in a different form. While this change likely improves JAX compatibility and potentially performance, please verify:
The mathematical equivalence of:
# Old gr_tmp = xp.einsum("lni,lnj->lij", gg, tr) # New gr_tmp = xp.sum(gg[:, :, :, None] * tr[:, :, None, :], axis=1)The mathematical equivalence of:
# Old grrg = xp.einsum("flid,fljd->flij", gr, gr1) # New grrg = xp.sum(gr[:, :, :, None, :] * gr1[:, :, None, :, :], axis=4)Consider adding comments explaining the mathematical operations being performed to improve code readability, as the direct sum operations are less intuitive than einsum notation.
✅ Verification successful
Looking at the code changes and search results, I can now generate a final response:
Mathematical equivalence verified for einsum replacement
The changes replacing
einsumwith directsumoperations are mathematically equivalent:
For
gr_tmpcomputation:
- Original:
xp.einsum("lni,lnj->lij", gg, tr)performs matrix multiplication along the 'n' axis- New:
xp.sum(gg[:, :, :, None] * tr[:, :, None, :], axis=1)does the same by:
- Adding broadcast dimensions with
None- Multiplying aligned tensors
- Summing along the correct axis
For
grrgcomputation:
- Original:
xp.einsum("flid,fljd->flij", gr, gr1)performs matrix multiplication along the 'd' axis- New:
xp.sum(gr[:, :, :, None, :] * gr1[:, :, None, :, :], axis=4)achieves the same through explicit broadcasting and summationThe changes improve JAX compatibility while maintaining the same mathematical operations, just expressed differently.
🏁 Scripts executed
The following scripts were executed for the analysis:
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#!/bin/bash # Description: Search for any existing tests that verify the descriptor computation # Test: Look for test files that might contain verification of these operations rg -l "DescrptSeAArrayAPI.*call" --type pyLength of output: 44
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#!/bin/bash # Let's try a broader search for test files related to descriptor computation rg -l "DescrptSeA" --type py tests/ # Also search for test files containing 'einsum' to find relevant test cases rg -l "einsum" --type py tests/ # Look for the actual implementation to understand the context better rg -l "class DescrptSeA" --type pyLength of output: 671
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#!/bin/bash # Search for any numerical testing or comparison functions rg "assert.*allclose|assert.*almost_equal" --type py tests/Length of output: 108
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#!/bin/bash # Look for the actual implementation of the descriptor computation ast-grep --pattern 'def _compute_descriptor($$$)'Length of output: 51
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#!/bin/bash # Let's look at the test files in the correct location rg -l "DescrptSeA" source/tests/ # Check the implementation in the JAX version since the changes are JAX-related rg -B 5 -A 5 "einsum|sum.*axis" deepmd/jax/descriptor/se_e2_a.py # Look at the implementation in the file being reviewed rg -B 5 -A 5 "einsum|sum.*axis" deepmd/dpmodel/descriptor/se_e2_a.pyLength of output: 4221
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#!/bin/bash # Look for any numerical testing in the source/tests directory rg "assert.*allclose|assert.*almost_equal" source/tests/Length of output: 111515
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#!/bin/bash # Let's look at the test files specifically for se_e2_a descriptor rg -B 5 -A 5 "einsum|sum.*axis" source/tests/array_api_strict/descriptor/se_e2_a.py source/tests/consistent/descriptor/test_se_e2_a.py # Also check for any numerical comparison tests for this descriptor rg "assert.*allclose|assert.*almost_equal" source/tests/array_api_strict/descriptor/se_e2_a.py source/tests/consistent/descriptor/test_se_e2_a.pyLength of output: 284
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#!/bin/bash # Look for any implementation comparisons between different array libraries rg -l "test_se_e2_a" source/tests/consistent/Length of output: 45
deepmd/jax/utils/serialization.py (4)
6-16: LGTM: New imports correctly integrate necessary modulesThe added imports for
numpy,orbax.checkpoint, andjax_exportare appropriate and essential for handling.hlofiles and exporting models. They integrate well with the existing codebase.
49-86: LGTM: Proper implementation of.hlofile handling indeserialize_to_fileThe new conditional branch effectively handles models with the
.hloextension. The serialization process correctly usesjax_exportto export the model and updates thedatadictionary with serialized information and model constants. This addition enhances the utility by supporting more model formats.
54-69: Verify the handling of optional parameters in model exportThe conditional inclusion of
fparamandaparambased onmodel.get_dim_fparam()andmodel.get_dim_aparam()may skip parameters when the dimensions are zero orNone. Ensure this behavior aligns with the intended model export logic, especially when dimensions are zero but parameters are still required.Would you like to run a verification script to confirm that models with zero-dimensional parameters are correctly exported?
141-145: LGTM: Correct deserialization logic for.hlofiles inserialize_from_fileThe added branch appropriately handles the deserialization of
.hlofiles by loading the model data and removing unnecessary entries from thedatadictionary. This ensures compatibility with the serialization logic.deepmd/jax/infer/deep_eval.py (1)
385-388: Clarify the output shape calculation for atomic outputs.There's a commented-out line with a note "Something wrong here?" indicating uncertainty about the correct output shape in the
_get_output_shapemethod forOutputVariableCategory.OUT. Please verify that the current implementation is correct and remove the commented-out code if it's no longer needed.
![github-advanced-security[bot]](https://avatars.githubusercontent.com/in/57789?s=60&v=4){kind=small}
| @@ -39,6 +46,44 @@ | |||
| model_def_script=ocp.args.JsonSave(model_def_script), | |||
| ), | |||
| ) | |||
| elif model_file.endswith(".hlo"): | |||
| model = BaseModel.deserialize(data["model"]) | |||
| model_def_script = data["model_def_script"] | |||
Check notice
Code scanning / CodeQL
Unused local variable Note
Codecov ReportAttention: Patch coverage is
Additional details and impacted files@@ Coverage Diff @@
## devel #4256 +/- ##
==========================================
- Coverage 84.37% 84.29% -0.08%
==========================================
Files 551 553 +2
Lines 51585 51820 +235
Branches 3052 3052
==========================================
+ Hits 43524 43683 +159
- Misses 7100 7175 +75
- Partials 961 962 +1 ☔ View full report in Codecov by Sentry. |
Signed-off-by: Jinzhe Zeng <[email protected]>
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Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (1)
deepmd/backend/jax.py (1)
74-78: LGTM: Consider enhancing docstringThe implementation correctly returns the DeepEval class. While the existing docstring is adequate, it could be enhanced to include details about the specific DeepEval implementation being used.
@property def deep_eval(self) -> type["DeepEvalBackend"]: """The Deep Eval backend of the backend. Returns ------- type[DeepEvalBackend] - The Deep Eval backend of the backend. + The JAX-based Deep Eval backend implementation for model evaluation. """ from deepmd.jax.infer.deep_eval import ( DeepEval, ) return DeepEval
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📒 Files selected for processing (1)
- deepmd/backend/jax.py (2 hunks)
🔇 Additional comments (2)
deepmd/backend/jax.py (2)
37-37: LGTM: Feature flag correctly updatedThe addition of
Backend.Feature.DEEP_EVALproperly aligns with the implementation of thedeep_evalproperty, resolving the previously identified inconsistency.
41-41: Verify handling of both file formatsThe addition of ".hlo" suffix is noted. Please ensure that both serialization hooks can properly handle both formats.
✅ Verification successful
Based on the search results, I can now generate the final response since I have sufficient information about how both formats are handled in the serialization code.
Both .hlo and .jax formats are properly handled in serialization
The serialization code in
deepmd/jax/utils/serialization.pyhas distinct handling paths for both formats:
.jaxfiles are handled usingBaseModel.deserialize()with checkpointing support.hlofiles are processed throughload_dp_model()with specific variable management🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that serialization code handles both .hlo and .jax formats # Search for format-specific handling in serialization code rg -A 5 "\.hlo|\.jax" --glob "deepmd/jax/utils/serialization.py"Length of output: 2909
Signed-off-by: Jinzhe Zeng <[email protected]>
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> Signed-off-by: Jinzhe Zeng <[email protected]>
Signed-off-by: Jinzhe Zeng <[email protected]>
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Actionable comments posted: 4
🧹 Outside diff range and nitpick comments (3)
deepmd/jax/utils/auto_batch_size.py (1)
44-59: Simplify the return statement inis_oom_error.The return statement can be simplified by returning the condition directly.
Apply this diff to simplify the code:
def is_oom_error(self, e: Exception) -> bool: """Check if the exception is an OOM error. Parameters ---------- e : Exception Exception """ # several sources think CUSOLVER_STATUS_INTERNAL_ERROR is another out-of-memory error, # such as https://github.com/JuliaGPU/CUDA.jl/issues/1924 # (the meaningless error message should be considered as a bug in cusolver) - if isinstance(e, (jaxlib.xla_extension.XlaRuntimeError, ValueError)) and ( - "RESOURCE_EXHAUSTED:" in e.args[0] - ): - return True - return False + return isinstance(e, (jaxlib.xla_extension.XlaRuntimeError, ValueError)) and ( + "RESOURCE_EXHAUSTED:" in e.args[0] + )🧰 Tools
🪛 Ruff
55-59: Return the condition directly
Inline condition
(SIM103)
deepmd/dpmodel/model/make_model.py (1)
227-236: Consider using consistent parameter passing styleWhile the implementation is correct, consider using consistent parameter passing style for better readability:
- coord=cc, - atype=atype, - box=bb, fparam=fp, aparam=ap, do_atomic_virial=do_atomic_virial, + coord=cc, + atype=atype, + box=bb,Group the required parameters together followed by optional parameters for better code organization.
deepmd/jax/infer/deep_eval.py (1)
366-368: Rephrase the in-code comment for professionalismThe comment
# this is kinda hackycan be rephrased to maintain a professional tone. Consider changing it to a more descriptive comment like# Assigning placeholder values when output is unavailable.Apply this diff to update the comment:
- ) # this is kinda hacky + ) # Assigning placeholder values when output is unavailable
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📒 Files selected for processing (4)
- deepmd/dpmodel/model/make_model.py (3 hunks)
- deepmd/jax/infer/deep_eval.py (1 hunks)
- deepmd/jax/model/hlo.py (1 hunks)
- deepmd/jax/utils/auto_batch_size.py (1 hunks)
🧰 Additional context used
🪛 Ruff
deepmd/jax/infer/deep_eval.py
303-306: Use ternary operator
natoms = len(atom_types[0]) if mixed_type else len(atom_types)instead ofif-else-blockReplace
if-else-block withnatoms = len(atom_types[0]) if mixed_type else len(atom_types)(SIM108)
332-335: Use ternary operator
box_input = cells.reshape([-1, 3, 3]) if cells is not None else Noneinstead ofif-else-blockReplace
if-else-block withbox_input = cells.reshape([-1, 3, 3]) if cells is not None else None(SIM108)
deepmd/jax/utils/auto_batch_size.py
55-59: Return the condition directly
Inline condition
(SIM103)
🔇 Additional comments (6)
deepmd/jax/utils/auto_batch_size.py (3)
1-11: LGTM! Clean file structure and imports.The file has proper licensing, clean imports, and clear class inheritance structure.
24-32: LGTM! Well-structured constructor.The constructor is properly documented with clear parameter descriptions and correctly calls the parent class initialization.
34-42: LGTM! Effective GPU availability check.The implementation is simple and effective, with proper type hints and documentation.
deepmd/dpmodel/model/make_model.py (3)
3-3: LGTM: Type hint import additionThe addition of
Callablefrom typing module is appropriate for type-hinting the function parameter.
43-129: Well-structured function extraction with good practicesThe new
model_call_from_call_lowerfunction demonstrates:
- Clear separation of concerns
- Comprehensive documentation
- Strong type hints
- Logical flow of operations
43-129: Verify integration with other componentsLet's verify the usage of this new function across the codebase:
✅ Verification successful
Refactoring is properly integrated and used
The function
model_call_from_call_loweris correctly integrated into the codebase:
- It's imported and used in
deepmd/jax/model/hlo.py- The implementation is consistent with its usage
- The git history shows this is a refactoring that maintains the same functionality
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Script:
#!/bin/bash # Search for other potential uses of model_call_from_call_lower rg "model_call_from_call_lower" --type python # Search for other implementations of similar functionality that might need refactoring ast-grep --pattern 'def call($params) { $$$ normalize_coord($$$) $$$ extend_coord_with_ghosts($$$) $$$ }'Length of output: 194
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#!/bin/bash # Search for usages of model_call_from_call_lower without file type flag rg "model_call_from_call_lower" # Search for similar patterns in Python files rg "normalize_coord.*extend_coord_with_ghosts" -A 5 # Look for imports of this function rg "from.*make_model.*import.*model_call_from_call_lower"Length of output: 426
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#!/bin/bash # Check the context of usage in hlo.py rg -B 5 -A 10 "model_call_from_call_lower" deepmd/jax/model/hlo.py # Check if this is a new file or modification by looking at git history git log -p deepmd/dpmodel/model/make_model.py | grep -A 10 "model_call_from_call_lower" # Look for any similar patterns in the codebase rg "normalize_coord|extend_coord_with_ghosts|build_neighbor_list" --no-filenameLength of output: 1660
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> Signed-off-by: Jinzhe Zeng <[email protected]>
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Actionable comments posted: 5
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📒 Files selected for processing (1)
- deepmd/jax/infer/deep_eval.py (1 hunks)
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deepmd/jax/infer/deep_eval.py
303-306: Use ternary operator
natoms = len(atom_types[0]) if mixed_type else len(atom_types)instead ofif-else-blockReplace
if-else-block withnatoms = len(atom_types[0]) if mixed_type else len(atom_types)(SIM108)
332-335: Use ternary operator
box_input = cells.reshape([-1, 3, 3]) if cells is not None else Noneinstead ofif-else-blockReplace
if-else-block withbox_input = cells.reshape([-1, 3, 3]) if cells is not None else None(SIM108)
Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com> Signed-off-by: Jinzhe Zeng <[email protected]>
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Signed-off-by: Jinzhe Zeng <[email protected]>
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Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (3)
deepmd/dpmodel/model/make_model.py (1)
43-129: Add input validation for better error handling
While the implementation is solid, consider adding input validation to handle edge cases:
- Validate that input arrays have correct shapes and types
- Check if
sellist is non-empty - Ensure
rcutis positive
Example validation:
def model_call_from_call_lower(
*, # enforce keyword-only arguments
call_lower: Callable[
[
np.ndarray,
np.ndarray,
np.ndarray,
Optional[np.ndarray],
Optional[np.ndarray],
bool,
],
dict[str, np.ndarray],
],
rcut: float,
sel: list[int],
mixed_types: bool,
model_output_def: ModelOutputDef,
coord: np.ndarray,
atype: np.ndarray,
box: Optional[np.ndarray] = None,
fparam: Optional[np.ndarray] = None,
aparam: Optional[np.ndarray] = None,
do_atomic_virial: bool = False,
):
+ if not isinstance(coord, np.ndarray) or not isinstance(atype, np.ndarray):
+ raise TypeError("coord and atype must be numpy arrays")
+ if not sel:
+ raise ValueError("sel list cannot be empty")
+ if rcut <= 0:
+ raise ValueError("rcut must be positive")
nframes, nloc = atype.shape[:2]deepmd/jax/infer/deep_eval.py (2)
162-165: Add missing return type annotations
The methods get_has_efield and get_ntypes_spin lack return type annotations. Including return type annotations improves code readability and enables better type checking.
Apply this diff to add the return type annotations:
-def get_has_efield(self):
+def get_has_efield(self) -> bool:
"""Check if the model has efield."""
return False
-def get_ntypes_spin(self):
+def get_ntypes_spin(self) -> int:
"""Get the number of spin atom types of this model."""
return 0Also applies to: 166-169
347-348: Clarify or remove commented-out code
The commented-out code and accompanying comment may cause confusion:
# it seems not doing conversion
# dp_name = self._OUTDEF_DP2BACKEND[odef.name]Please consider clarifying the intent behind this code or removing it if it's no longer needed.
Apply this diff to remove the commented-out code:
- # it seems not doing conversion
- # dp_name = self._OUTDEF_DP2BACKEND[odef.name]
dp_name = odef.name📜 Review details
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Review profile: CHILL
📒 Files selected for processing (6)
- deepmd/backend/jax.py (2 hunks)
- deepmd/dpmodel/descriptor/se_e2_a.py (1 hunks)
- deepmd/dpmodel/model/make_model.py (3 hunks)
- deepmd/jax/env.py (2 hunks)
- deepmd/jax/infer/deep_eval.py (1 hunks)
- source/tests/consistent/io/test_io.py (2 hunks)
🚧 Files skipped from review as they are similar to previous changes (4)
- deepmd/backend/jax.py
- deepmd/dpmodel/descriptor/se_e2_a.py
- deepmd/jax/env.py
- source/tests/consistent/io/test_io.py
🧰 Additional context used
🪛 Ruff
deepmd/jax/infer/deep_eval.py
303-306: Use ternary operator natoms = len(atom_types[0]) if mixed_type else len(atom_types) instead of if-else-block
Replace if-else-block with natoms = len(atom_types[0]) if mixed_type else len(atom_types)
(SIM108)
332-335: Use ternary operator box_input = cells.reshape([-1, 3, 3]) if cells is not None else None instead of if-else-block
Replace if-else-block with box_input = cells.reshape([-1, 3, 3]) if cells is not None else None
(SIM108)
🔇 Additional comments (3)
deepmd/dpmodel/model/make_model.py (3)
1-4: LGTM: Import changes enhance type safety
The addition of Callable from typing module improves type safety and documentation of function signatures.
227-238: LGTM: Well-structured refactoring
The refactoring of the call method improves code organization by:
- Separating complex logic into a dedicated function
- Maintaining clear parameter passing
- Preserving existing functionality
227-238: Verify impact on existing callers
Let's ensure all callers are compatible with the refactored implementation.
✅ Verification successful
Let me analyze the search results. The code shows that the call method is used in various test files and model implementations. The changes in make_model.py involve refactoring the model_call_from_call_lower function. Looking at the test files, they primarily use the call method for testing purposes and comparing outputs between different implementations.
Let me verify if there are any direct usages of model_call_from_call_lower in the codebase:
Let me check the implementation in jax/model/hlo.py to understand how it uses the refactored function:
Based on the analysis of the codebase, I can now provide the final response:
Changes to model_call_from_call_lower are properly synchronized
The refactored implementation in make_model.py is correctly synchronized with its only other usage in jax/model/hlo.py. Both implementations use the same parameter structure and calling convention. The changes are localized to these two files and all test cases that exercise this functionality continue to use the stable call interface.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for direct calls to CM.call method
rg -l "\.call\s*\(" | while read -r file; do
if [[ "$file" != "deepmd/dpmodel/model/make_model.py" ]]; then
echo "=== $file ==="
rg -A 5 "\.call\s*\(" "$file"
fi
done
Length of output: 20616
Script:
#!/bin/bash
# Search for direct usages of model_call_from_call_lower
rg "model_call_from_call_lower"
Length of output: 312
Script:
#!/bin/bash
# Check the implementation in jax/model/hlo.py
rg -A 10 "model_call_from_call_lower" deepmd/jax/model/hlo.py
Length of output: 633
Signed-off-by: Jinzhe Zeng <[email protected]>
Summary by CodeRabbit
Release Notes
New Features
.hlofile extensions in model loading and saving functionalities.DeepEvalclass for enhanced deep learning model evaluation in molecular simulations.HLOclass for managing model predictions within a deep learning framework.Bug Fixes
Documentation
Chores