added mm_einsum

[ziofil]

User description

Context:
mm_einsum for contracting a TN made of CV and Fock components

Description of the Change:
For now just the mm_einsum.py file

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PR Type

enhancement, documentation

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Description

• Introduced a new module mm_einsum.py for contracting tensor networks composed of continuous-variable (CV) and Fock components.
• Implemented functions to calculate contraction costs and determine optimal contraction paths.
• Enhanced performance using Numba's njit for just-in-time compilation.
• Provided comprehensive docstrings to explain the functionality and usage of each function.

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PRDescriptionHeader.CHANGES_WALKTHROUGH

	Relevant files
Enhancement	mm_einsum.py Implement `mm_einsum` for tensor network contraction          mrmustard/physics/mm_einsum.py Implemented mm_einsum for contracting tensor networks with CV and Fock components. Added functions for calculating contraction costs and optimal paths. Included detailed docstrings for all functions. Utilized Numba for performance optimization. +211/-0

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PR Reviewer Guide 🔍

Here are some key observations to aid the review process:

⏱️ Estimated effort to review: 4 🔵🔵🔵🔵⚪

🏅 Score: 92

🧪 No relevant tests

🔒 No security concerns identified

⚡ Recommended focus areas for review Performance Optimization The optimal function uses an exhaustive search algorithm which may become inefficient for large tensor networks. Consider implementing a heuristic approach or using dynamic programming for better scalability. Error Handling The code lacks explicit error handling for potential edge cases, such as empty input lists or invalid Fock dimensions. Consider adding appropriate error checks and exception handling.

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In the optimal function, consider adding a timeout mechanism or a maximum iteration limit to prevent potential infinite loops or excessive runtime for very large input sets. This would improve the robustness of the function. [important]

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PR Code Suggestions ✨

Explore these optional code suggestions:

Category	Suggestion	Score
Performance	Use built-in Python functions for simple mathematical operations to reduce dependencies and improve performance Consider using math.prod() instead of np.prod() for calculating the product of integers. It's more efficient for small sequences and doesn't require importing NumPy. mrmustard/physics/mm_einsum.py [86] -fock_flops = np.prod(fock_contracted_shape) * np.prod(fock_remaining_shape) +from math import prod +fock_flops = prod(fock_contracted_shape) * prod(fock_remaining_shape) Apply this suggestion Suggestion importance[1-10]: 7 Why: The suggestion to use math.prod() instead of np.prod() is valid as it reduces dependency on NumPy for simple integer operations, which can improve performance and readability for small sequences.	7
Best practice	Use descriptive variable names to enhance code readability and self-documentation Consider using a more descriptive variable name instead of m in the _CV_flops function to improve code readability. mrmustard/physics/mm_einsum.py [21-28] @njit -def _CV_flops(nA: int, nB: int, m: int) -> int: +def _CV_flops(nA: int, nB: int, num_contracted_cv: int) -> int: """Calculate the cost of contracting two tensors with CV indices. Args: nA: Number of CV indices in the first tensor nB: Number of CV indices in the second tensor - m: Number of CV indices involved in the contraction + num_contracted_cv: Number of CV indices involved in the contraction """ Apply this suggestion Suggestion importance[1-10]: 6 Why: Renaming the variable m to num_contracted_cv improves code readability by making the purpose of the variable clearer, which is a good practice for maintainability.	6
	Use named constants for magic values to improve code clarity and maintainability Consider using a constant for the infinity value in the optimal function instead of float("inf") to improve readability and maintainability. mrmustard/physics/mm_einsum.py [162] -best_flops: int = float("inf") +import math +INFINITY = math.inf +best_flops: int = INFINITY + Apply this suggestion Suggestion importance[1-10]: 5 Why: Using a named constant for infinity improves code readability and maintainability by avoiding magic numbers, although the impact is relatively minor.	5
Enhancement	Use defaultdict to simplify dictionary access and avoid explicit key existence checks Consider using collections.defaultdict for fock_size_dict to simplify the logic in the attempt_decomposition function and avoid potential KeyError exceptions. mrmustard/physics/mm_einsum.py [100-114] +from collections import defaultdict + def attempt_decomposition( - indices: set[int], fock_size_dict: dict[int, int] + indices: set[int], fock_size_dict: defaultdict[int, int] ) -> tuple[set[int], int]: """Attempt to reduce the number of indices by combining Fock indices when possible. Only possible if there is only one CV index and multiple Fock indices. Args: indices: Set of indices to potentially decompose - fock_size_dict: Dictionary mapping indices to their sizes + fock_size_dict: DefaultDict mapping indices to their sizes, with a default value of 0 Returns: Tuple of (decomposed indices, cost of decomposition) """ - fock_indices_shape = [fock_size_dict[idx] for idx in indices if idx in fock_size_dict] - cv_indices = [idx for idx in indices if idx not in fock_size_dict] + fock_indices_shape = [fock_size_dict[idx] for idx in indices if fock_size_dict[idx] != 0] + cv_indices = [idx for idx in indices if fock_size_dict[idx] == 0] Apply this suggestion Suggestion importance[1-10]: 4 Why: The suggestion to use defaultdict can simplify the code by removing the need for explicit key checks, but it introduces a new dependency and changes the logic slightly, which may not be necessary if the current implementation is already clear and correct.	4

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Codecov Report

Attention: Patch coverage is 0% with 59 lines in your changes missing coverage. Please review.

Project coverage is 88.87%. Comparing base (e5c02ce) to head (01b56e7).

Files with missing lines	Patch %	Lines
mrmustard/physics/mm_einsum.py	0.00%	59 Missing ⚠️

Additional details and impacted files

@@             Coverage Diff             @@
##           develop     #515      +/-   ##
===========================================
- Coverage    89.77%   88.87%   -0.90%     
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  Files           92       93       +1     
  Lines         6054     6113      +59     
===========================================
- Hits          5435     5433       -2     
- Misses         619      680      +61     

Files with missing lines	Coverage Δ
mrmustard/physics/mm_einsum.py	0.00% <0.00%> (ø)

... and 1 file with indirect coverage changes

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