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@codeflash-ai codeflash-ai bot commented May 21, 2025

📄 9% (0.09x) speedup for NpzIOStore.make in keras/src/saving/saving_lib.py

⏱️ Runtime : 990 microseconds 909 microseconds (best of 320 runs)

📝 Explanation and details

Here is an optimized version of your NpzIOStore class.
The relevant hot path from the profiler is the make() method, which is dominated by two dict assignments and a read.
This is already very efficient, so only micro-optimizations are possible, but we can reduce duplicate lookups by storing variables and slightly streamline the logic to avoid repeated dictionary indexing.
with all comments preserved.

Optimization notes

  • Avoid multiple dictionary indexing by assigning the output dictionary {} to a variable val, and then assigning and returning it directly. This removes one lookup and assignment per call.
  • The class logic and all comments are untouched except for code in make.
  • This is highly efficient already. For further optimization, consider using a specialized dictionary or alternative structure only if profiling demonstrates real-world need.

No change to function signatures, return values, or behavior.
This is the fastest Python dictionary-based way to do what your method requires.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 5184 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 🔘 None Found
📊 Tests Coverage 100.0%
🌀 Generated Regression Tests Details
import numpy as np
# imports
import pytest  # used for our unit tests
from keras.src.saving.saving_lib import NpzIOStore

# unit tests

# --- Basic Test Cases ---

def test_make_creates_empty_dict_with_path():
    # Test that make creates an empty dict at the given path
    store = NpzIOStore("dummy.npz", mode="w")
    codeflash_output = store.make("foo"); result = codeflash_output

def test_make_returns_same_dict_reference():
    # Test that repeated calls to make with the same path overwrite and return new dict
    store = NpzIOStore("dummy.npz", mode="w")
    codeflash_output = store.make("bar"); d1 = codeflash_output
    d1["x"] = 1
    codeflash_output = store.make("bar"); d2 = codeflash_output

def test_make_with_empty_path_creates_root():
    # Test that make with empty path creates __root__ key
    store = NpzIOStore("dummy.npz", mode="w")
    codeflash_output = store.make(""); result = codeflash_output

def test_make_with_none_path_creates_root():
    # Test that make with None path creates __root__ key
    store = NpzIOStore("dummy.npz", mode="w")
    codeflash_output = store.make(None); result = codeflash_output

def test_make_with_metadata_argument_ignored():
    # Test that metadata argument is ignored and does not affect result
    store = NpzIOStore("dummy.npz", mode="w")
    codeflash_output = store.make("baz", metadata={"foo": "bar"}); result = codeflash_output

# --- Edge Test Cases ---

def test_make_with_existing_key_overwrites():
    # Test that make overwrites existing key with new empty dict
    store = NpzIOStore("dummy.npz", mode="w")
    store.contents["dup"] = {"a": 1}
    codeflash_output = store.make("dup"); result = codeflash_output

def test_make_with_special_characters_in_path():
    # Test that make works with special characters in path
    store = NpzIOStore("dummy.npz", mode="w")
    special_path = "spécial/路径/!@#"
    codeflash_output = store.make(special_path); result = codeflash_output

def test_make_with_integer_path():
    # Test that make works with non-string path (e.g., integer)
    store = NpzIOStore("dummy.npz", mode="w")
    codeflash_output = store.make(123); result = codeflash_output

def test_make_with_tuple_path():
    # Test that make works with tuple path
    store = NpzIOStore("dummy.npz", mode="w")
    path = ("a", "b")
    codeflash_output = store.make(path); result = codeflash_output

def test_make_with_falsey_nonempty_path():
    # Test that make with path=0 creates a key "0" (since 0 is falsey but not empty string)
    store = NpzIOStore("dummy.npz", mode="w")
    codeflash_output = store.make(0); result = codeflash_output

def test_make_does_not_affect_other_keys():
    # Test that make does not modify other keys in contents
    store = NpzIOStore("dummy.npz", mode="w")
    store.contents["a"] = {"val": 1}
    store.contents["b"] = {"val": 2}
    store.make("c")

def test_make_with_large_key():
    # Test that make works with a very long string as key
    store = NpzIOStore("dummy.npz", mode="w")
    long_key = "x" * 500
    codeflash_output = store.make(long_key); result = codeflash_output

# --- Large Scale Test Cases ---

def test_make_many_unique_keys():
    # Test that make can handle many unique keys
    store = NpzIOStore("dummy.npz", mode="w")
    for i in range(1000):
        codeflash_output = store.make(f"key_{i}"); result = codeflash_output

def test_make_overwrite_many_times():
    # Test that repeatedly overwriting the same key always yields empty dict
    store = NpzIOStore("dummy.npz", mode="w")
    for i in range(1000):
        codeflash_output = store.make("repeat"); result = codeflash_output

def test_make_with_large_keys_and_values():
    # Test that make can handle large keys and does not leak references
    store = NpzIOStore("dummy.npz", mode="w")
    # Add 500 large keys, then overwrite them
    for i in range(500):
        key = "k" * (i+1)
        store.make(key)
    for i in range(500):
        key = "k" * (i+1)
        codeflash_output = store.make(key); result = codeflash_output

def test_make_with_various_types_as_keys():
    # Test that make can handle various hashable types as keys
    store = NpzIOStore("dummy.npz", mode="w")
    keys = [
        42,
        3.14,
        (1, 2, 3),
        frozenset([1, 2]),
        True,
        b"bytes",
    ]
    for key in keys:
        codeflash_output = store.make(key); result = codeflash_output

def test_make_scalability_with_large_dict():
    # Test that make does not slow down or error with a large contents dict
    store = NpzIOStore("dummy.npz", mode="w")
    for i in range(999):
        store.contents[f"pre_{i}"] = {"dummy": i}
    codeflash_output = store.make("final_key"); result = codeflash_output
    # Ensure pre-existing keys are untouched
    for i in range(999):
        pass
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

import io

import numpy as np
# imports
import pytest  # used for our unit tests
from keras.src.saving.saving_lib import NpzIOStore

# unit tests

# Helper to create an NpzIOStore in write mode for tests
@pytest.fixture
def store():
    # Use a dummy root_path since we won't be writing to disk
    return NpzIOStore("dummy.npz", mode="w")

# ---------------------------
# 1. BASIC TEST CASES
# ---------------------------

def test_make_creates_new_key(store):
    # Should create an empty dict at the given path
    codeflash_output = store.make("foo"); result = codeflash_output

def test_make_returns_same_dict_on_repeat(store):
    # Should overwrite existing key with new empty dict each time
    codeflash_output = store.make("bar"); d1 = codeflash_output
    d1["a"] = 1
    codeflash_output = store.make("bar"); d2 = codeflash_output

def test_make_with_empty_path_creates_root(store):
    # Should create a special __root__ key for empty path
    codeflash_output = store.make(""); result = codeflash_output

def test_make_with_none_path_creates_root(store):
    # Should treat None as empty and create __root__
    codeflash_output = store.make(None); result = codeflash_output

def test_make_with_metadata_ignored(store):
    # Should ignore metadata and still create empty dict
    codeflash_output = store.make("baz", metadata={"foo": "bar"}); result = codeflash_output

def test_make_multiple_keys(store):
    # Should create multiple keys independently
    codeflash_output = store.make("a"); d1 = codeflash_output
    codeflash_output = store.make("b"); d2 = codeflash_output

# ---------------------------
# 2. EDGE TEST CASES
# ---------------------------

def test_make_with_special_characters(store):
    # Should allow keys with special characters
    key = "weird!@#$%^&*()_+-=|\\/?><,.;:'\"[]{}"
    codeflash_output = store.make(key); result = codeflash_output

def test_make_with_long_key(store):
    # Should allow long keys up to a reasonable length
    key = "x" * 255
    codeflash_output = store.make(key); result = codeflash_output

def test_make_overwrites_existing_key(store):
    # Should overwrite existing key with new empty dict
    codeflash_output = store.make("dup"); d1 = codeflash_output
    d1["foo"] = 123
    codeflash_output = store.make("dup"); d2 = codeflash_output

def test_make_with_integer_path(store):
    # Should convert integer path to string and use as key
    codeflash_output = store.make(123); result = codeflash_output

def test_make_with_tuple_path(store):
    # Should allow tuple as key
    key = (1, 2, 3)
    codeflash_output = store.make(key); result = codeflash_output

def test_make_with_falsey_nonempty_path(store):
    # Should treat 0 as a valid key, not as empty
    codeflash_output = store.make(0); result = codeflash_output

def test_make_with_path_collision_with_root(store):
    # Should allow "__root__" as a user key (distinct from empty path)
    codeflash_output = store.make("__root__"); result = codeflash_output
    # If we now call with empty path, it should overwrite __root__
    codeflash_output = store.make(""); result2 = codeflash_output

def test_make_with_path_as_bytes(store):
    # Should allow bytes as key
    key = b"byteskey"
    codeflash_output = store.make(key); result = codeflash_output

# ---------------------------
# 3. LARGE SCALE TEST CASES
# ---------------------------

def test_make_many_keys(store):
    # Should handle creating many keys (stress test)
    n = 1000
    for i in range(n):
        k = f"key_{i}"
        codeflash_output = store.make(k); result = codeflash_output

def test_make_many_keys_and_overwrite(store):
    # Should overwrite all keys and ensure all are empty dicts
    n = 500
    for i in range(n):
        k = f"key_{i}"
        codeflash_output = store.make(k); d = codeflash_output
        d["foo"] = i
    # Now overwrite all
    for i in range(n):
        k = f"key_{i}"
        codeflash_output = store.make(k); d = codeflash_output

def test_make_with_large_key_size(store):
    # Should handle a very large string as key
    key = "a" * 1000
    codeflash_output = store.make(key); result = codeflash_output

def test_make_with_large_metadata(store):
    # Should ignore large metadata and still create empty dict
    metadata = {str(i): i for i in range(1000)}
    codeflash_output = store.make("bigmeta", metadata=metadata); result = codeflash_output

def test_make_with_large_number_of_root_calls(store):
    # Should allow repeated calls to make with empty path
    for _ in range(100):
        codeflash_output = store.make(""); result = codeflash_output

# ---------------------------
# 4. NEGATIVE AND TYPE ERROR CASES
# ---------------------------

def test_make_with_unhashable_key_raises(store):
    # Should raise TypeError if key is unhashable (e.g., list)
    with pytest.raises(TypeError):
        store.make([1, 2, 3])

def test_make_with_dict_key_raises(store):
    # Should raise TypeError if key is a dict (unhashable)
    with pytest.raises(TypeError):
        store.make({"a": 1})

def test_make_with_set_key_raises(store):
    # Should raise TypeError if key is a set (unhashable)
    with pytest.raises(TypeError):
        store.make(set([1, 2, 3]))

def test_make_with_path_none_and_metadata(store):
    # Should create __root__ even if metadata is present and path is None
    codeflash_output = store.make(None, metadata={"foo": "bar"}); result = codeflash_output
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.

To edit these changes git checkout codeflash/optimize-NpzIOStore.make-maxylkzk and push.

Codeflash

Here is an optimized version of your `NpzIOStore` class.  
The relevant hot path from the profiler is the [`make()`](#) method, which is dominated by two dict assignments and a read.  
This is already very efficient, so only micro-optimizations are possible, but we can reduce duplicate lookups by storing variables and slightly streamline the logic to avoid repeated dictionary indexing.
 **with all comments preserved**.



### Optimization notes

- Avoid multiple dictionary indexing by assigning the output dictionary `{}` to a variable `val`, and then assigning and returning it directly. This removes one lookup and assignment per call.
- The class logic and all comments are untouched except for code in `make`.
- This is highly efficient already. For further optimization, consider using a specialized dictionary or alternative structure only if profiling demonstrates real-world need.

**No change to function signatures, return values, or behavior.**  
This is the fastest Python dictionary-based way to do what your method requires.
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label May 21, 2025
@codeflash-ai codeflash-ai bot requested a review from HeshamHM28 May 21, 2025 13:08
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