+
+▶ code
+▼ output
+ ▶ uv-logs
+ |
+Cell: combine | 4.46s
+ |
+
+Raw
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+# /// script
+# requires-python = ">=3.10"
+# dependencies = [
+# "numpy",
+# "torch==2.8.0",
+# "kernels-benchmark-tools",
+# "matplotlib",
+# ]
+#
+# [tool.uv.sources]
+# kernels-benchmark-tools = { path = "../../../../../tools", editable = true }
+# ///
+from kernels_benchmark_tools.core.visuals import generate_combined_results
+
+# Map display names to uvnote environment variables
+cache_env_map = {
+ "HF Kernels SwiGLU": "UVNOTE_FILE_HF_KERNELS_SWIGLU_BENCHMARK",
+ "PyTorch SwiGLU": "UVNOTE_FILE_TORCH_SWIGLU_BENCHMARK",
+ "Compiled SwiGLU": "UVNOTE_FILE_COMPILED_SWIGLU_BENCHMARK",
+}
+
+# Generate combined results with visualization
+generate_combined_results(
+ cache_env_map=cache_env_map,
+ output_filename="activation.jsonl",
+ svg_filename="latency.svg"
+)
+
+
+
+====================================================================== +LOADING BENCHMARK DATA +====================================================================== +✓ HF Kernels SwiGLU : /__w/kernels-benchmarks/kernels-benchmarks/benches/activation/impls/.uvnote/cache/6224da41d19be71ba3c3e08faf8e070edc78f006ff38223679e2e3468efc8e90 +✓ PyTorch SwiGLU : /__w/kernels-benchmarks/kernels-benchmarks/benches/activation/impls/.uvnote/cache/a40c475de184c807594b99c7eea02ce02fe459cd22e0d785b1ac4d16a6d993c6 +✓ Compiled SwiGLU : /__w/kernels-benchmarks/kernels-benchmarks/benches/activation/impls/.uvnote/cache/ba5cb86f85bd22735ed4bf8a7eae177b0ff2e4bc554b5444da233340a6935d72 + + ✓ Found HF Kernels SwiGLU + Path: /__w/kernels-benchmarks/kernels-benchmarks/benches/activation/impls/.uvnote/cache/6224da41d19be71ba3c3e08faf8e070edc78f006ff38223679e2e3468efc8e90/activation.jsonl + ✓ Found PyTorch SwiGLU + Path: /__w/kernels-benchmarks/kernels-benchmarks/benches/activation/impls/.uvnote/cache/a40c475de184c807594b99c7eea02ce02fe459cd22e0d785b1ac4d16a6d993c6/activation.jsonl + ✓ Found Compiled SwiGLU + Path: /__w/kernels-benchmarks/kernels-benchmarks/benches/activation/impls/.uvnote/cache/ba5cb86f85bd22735ed4bf8a7eae177b0ff2e4bc554b5444da233340a6935d72/activation.jsonl + +====================================================================== +Summary: 3 found, 0 skipped, 0 missing +====================================================================== + +COMBINED BENCHMARK SUMMARY + +impl wl p50(ms) ok +compiled_swiglu_max_autotune llama_T512_D11008 0.11 True +compiled_swiglu_max_autotune llama_T512_D4096 0.10 True +compiled_swiglu_max_autotune llama_T512_D8192 0.11 True +hf_kernels_swiglu llama_T512_D11008 0.03 True +hf_kernels_swiglu llama_T512_D4096 0.02 True +hf_kernels_swiglu llama_T512_D8192 0.03 True +torch_swiglu llama_T512_D11008 0.05 True +torch_swiglu llama_T512_D4096 0.04 True +torch_swiglu llama_T512_D8192 0.05 True + +GENERATING COMBINED VISUALIZATION + +Loaded 9 records +✓ Visualization saved as latency.svg +Saved latency.png +✓ Visualization saved as latency.svg +✓ SVG visualization ready! + +ANALYSIS COMPLETE +Total implementations analyzed: 3 + +Implementations included: + ✓ HF Kernels SwiGLU + ✓ PyTorch SwiGLU + ✓ Compiled SwiGLU +
+
+
+▶ UV Install Logs
+
+