Update benchmark results for 68984fb7

results/benchmarks.json

@@ -705,7 +705,7 @@
         "warmup_time": -1
     },
     "bench_numba.NumbaRadonCall.time_call": {
-        "code": "class NumbaRadonCall:\n    def time_call(self, cache):\n        self.fn(self.x)\n\n    def setup(self, cache):\n        _check_numba()\n        joined_inputs, [model_logp, model_dlogp] = create_radon_model()\n        rng = np.random.default_rng(1)\n        self.x = rng.normal(size=joined_inputs.type.shape).astype(config.floatX)\n        with config.change_flags(numba__cache=cache):\n            self.fn = function(\n                [joined_inputs],\n                [model_logp, model_dlogp],\n                mode=\"NUMBA\",\n                trust_input=True,\n            )\n        # Warmup\n        self.fn(self.x)",
+        "code": "class NumbaRadonCall:\n    def time_call(self, cache):\n        self.fn(self.x)\n\n    def setup(self, cache):\n        _check_numba()\n        if cache:\n            import tempfile\n    \n            import pytensor.link.numba.cache as cache_mod\n    \n            self._tmp_dir = tempfile.TemporaryDirectory()\n            self._orig_cache_path = cache_mod.NUMBA_CACHE_PATH\n            cache_mod.NUMBA_CACHE_PATH = Path(self._tmp_dir.name)\n        joined_inputs, [model_logp, model_dlogp] = create_radon_model()\n        rng = np.random.default_rng(1)\n        self.x = rng.normal(size=joined_inputs.type.shape).astype(config.floatX)\n        with config.change_flags(numba__cache=cache):\n            self.fn = function(\n                [joined_inputs],\n                [model_logp, model_dlogp],\n                mode=\"NUMBA\",\n                trust_input=True,\n            )\n        # Warmup\n        self.fn(self.x)",
         "min_run_count": 2,
         "name": "bench_numba.NumbaRadonCall.time_call",
         "number": 0,
@@ -723,11 +723,11 @@
         "sample_time": 0.01,
         "type": "time",
         "unit": "seconds",
-        "version": "65ef75c95e692b5c62d1c8397c0ae898f2f54cc16df51e8116b406668f2cd35f",
+        "version": "fc65e3c5fc34261c22a9079a44c16d204b6fb682515c10a6b833696fa8bb3356",
         "warmup_time": -1
     },
     "bench_numba.NumbaRadonCompile.time_compile_and_call": {
-        "code": "class NumbaRadonCompile:\n    def time_compile_and_call(self, cache):\n        with config.change_flags(numba__cache=cache):\n            fn = function(\n                [self.joined_inputs],\n                [self.model_logp, self.model_dlogp],\n                mode=\"NUMBA\",\n                trust_input=True,\n            )\n            fn(self.x)\n\n    def setup(self, cache):\n        _check_numba()\n        self.joined_inputs, [self.model_logp, self.model_dlogp] = create_radon_model()\n        rng = np.random.default_rng(1)\n        self.x = rng.normal(size=self.joined_inputs.type.shape).astype(config.floatX)\n        self.cache = cache",
+        "code": "class NumbaRadonCompile:\n    def time_compile_and_call(self, cache):\n        with config.change_flags(numba__cache=cache):\n            fn = function(\n                [self.joined_inputs],\n                [self.model_logp, self.model_dlogp],\n                mode=\"NUMBA\",\n                trust_input=True,\n            )\n            fn(self.x)\n\n    def setup(self, cache):\n        _check_numba()\n        if cache:\n            import tempfile\n    \n            import pytensor.link.numba.cache as cache_mod\n    \n            self._tmp_dir = tempfile.TemporaryDirectory()\n            self._orig_cache_path = cache_mod.NUMBA_CACHE_PATH\n            cache_mod.NUMBA_CACHE_PATH = Path(self._tmp_dir.name)\n        self.joined_inputs, [self.model_logp, self.model_dlogp] = create_radon_model()\n        rng = np.random.default_rng(1)\n        self.x = rng.normal(size=self.joined_inputs.type.shape).astype(config.floatX)",
         "min_run_count": 2,
         "name": "bench_numba.NumbaRadonCompile.time_compile_and_call",
         "number": 1,
@@ -745,7 +745,7 @@
         "sample_time": 0.01,
         "type": "time",
         "unit": "seconds",
-        "version": "2722e68555d9ea7a75a32a8f68ae585bb7572c1ff5ca1d41bdba2a99fe841532",
+        "version": "1619320e83423424972f7551b00068cb4ef4d062143d2415d4807bf9a11aa0ab",
         "warmup_time": -1
     },
     "bench_numba.NumbaScanSEIR.time_scan_seir": {

results/github-actions/68984fb7-existing-py_home_runner_micromamba_envs_pytensor-bench_bin_python.json

+{"commit_hash": "68984fb76e1eb35e225a88a0a6820259b95aa38c", "env_name": "existing-py_home_runner_micromamba_envs_pytensor-bench_bin_python", "date": 1773926630000, "params": {"machine": "github-actions", "python": "/home/runner/micromamba/envs/pytensor-bench/bin/python"}, "python": "/home/runner/micromamba/envs/pytensor-bench/bin/python", "requirements": {}, "env_vars": {}, "result_columns": ["result", "params", "version", "started_at", "duration", "stats_ci_99_a", "stats_ci_99_b", "stats_q_25", "stats_q_75", "stats_number", "stats_repeat", "samples", "profile"], "results": {"bench_graph.Traversal.time_traversal": [[8.428785166234136e-06, 9.199318257944037e-06, 1.2032023861167295e-05, 1.2893978513344889e-05, 4.5582913333343334e-05, 4.737475113108089e-05, 0.0001512925878382641, 0.00015526669718338512], [["'variable_ancestors'", "'variable_ancestors_with_blockers'", "'apply_ancestors'", "'apply_ancestors_with_blockers'", "'toposort'", "'toposort_with_blockers'", "'toposort_with_orderings'", "'toposort_with_orderings_and_blockers'"]], "695acd793b63fbc81a86536ec189d483d85fed356f3f12ddd163cad022bcc6dc", 1773960599470, 2.7625, [8.3245e-06, 9.0295e-06, 1.1826e-05, 1.2522e-05, 4.4991e-05, 4.6269e-05, 0.0001491, 0.00015285], [1.132e-05, 9.4558e-06, 1.2334e-05, 1.3119e-05, 5.2937e-05, 4.8193e-05, 0.00015749, 0.00016151], [8.3472e-06, 9.063e-06, 1.1959e-05, 1.2799e-05, 4.5415e-05, 4.6807e-05, 0.00015031, 0.00015362], [8.5417e-06, 9.2522e-06, 1.2247e-05, 1.2963e-05, 4.6104e-05, 4.7596e-05, 0.00015361, 0.00015674], [1173, 1194, 922, 861, 225, 221, 74, 71], [10, 10, 10, 10, 10, 10, 10, 10]], "bench_shape.Reshape.time_reshape": [[1.908229057372368e-06], [], "ba1db863e4f3131758d7ccd475f584b7596716d24f7884e41f09f1e6bd826668", 1773960600856, 2.5927, [1.8305e-06], [1.9674e-06], [1.8751e-06], [1.9198e-06], [5909], [10]]}, "durations": {"<build>": 4.410743713378906e-05}, "version": 2}
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