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pytensor
提交 17748b7d authored 作者: Ricardo Vieira's avatar Ricardo Vieira 提交者： Ricardo Vieira
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Remove accidental print statements

上级 4ac1e637
隐藏空白字符变更
内嵌 并排
正在显示 包含 161 行增加 和 168 行删除
pyproject.toml
浏览文件 @ 17748b7d
......@@ -129,7 +129,7 @@ exclude = ["doc/", "pytensor/_version.py"]
docstring-code-format = true
[tool.ruff.lint]
select = ["B905", "C", "E", "F", "I", "UP", "W", "RUF", "PERF", "PTH", "ISC"]
select = ["B905", "C", "E", "F", "I", "UP", "W", "RUF", "PERF", "PTH", "ISC", "T20"]
ignore = ["C408", "C901", "E501", "E741", "RUF012", "PERF203", "ISC001"]
unfixable = [
# zip-strict: the auto-fix adds `strict=False` but we might want `strict=True` instead
......@@ -144,7 +144,12 @@ lines-after-imports = 2
# TODO: Get rid of these:
"**/__init__.py" = ["F401", "E402", "F403"]
"pytensor/tensor/linalg.py" = ["F403"]
"pytensor/link/c/cmodule.py" = ["PTH"]
"pytensor/link/c/cmodule.py" = ["PTH", "T201"]
"pytensor/misc/elemwise_time_test.py" = ["T201"]
"pytensor/misc/elemwise_openmp_speedup.py" = ["T201"]
"pytensor/misc/check_duplicate_key.py" = ["T201"]
"pytensor/misc/check_blas.py" = ["T201"]
"pytensor/bin/pytensor_cache.py" = ["T201"]
# For the tests we skip because `pytest.importorskip` is used:
"tests/link/jax/test_scalar.py" = ["E402"]
"tests/link/jax/test_tensor_basic.py" = ["E402"]
......@@ -158,6 +163,8 @@ lines-after-imports = 2
"tests/sparse/test_sp2.py" = ["E402"]
"tests/sparse/test_utils.py" = ["E402"]
"tests/sparse/sandbox/test_sp.py" = ["E402", "F401"]
"tests/compile/test_monitormode.py" = ["T201"]
"scripts/run_mypy.py" = ["T201"]
[tool.mypy]
......
pytensor/breakpoint.py
浏览文件 @ 17748b7d
......@@ -108,14 +108,14 @@ class PdbBreakpoint(Op):
f"'{self.name}' could not be casted to NumPy arrays"
)
print("\n")
print("-------------------------------------------------")
print(f"Conditional breakpoint '{self.name}' activated\n")
print("The monitored variables are stored, in order,")
print("in the list variable 'monitored' as NumPy arrays.\n")
print("Their contents can be altered and, when execution")
print("resumes, the updated values will be used.")
print("-------------------------------------------------")
print("\n") # noqa: T201
print("-------------------------------------------------") # noqa: T201
print(f"Conditional breakpoint '{self.name}' activated\n") # noqa: T201
print("The monitored variables are stored, in order,") # noqa: T201
print("in the list variable 'monitored' as NumPy arrays.\n") # noqa: T201
print("Their contents can be altered and, when execution") # noqa: T201
print("resumes, the updated values will be used.") # noqa: T201
print("-------------------------------------------------") # noqa: T201
try:
import pudb
......
pytensor/compile/compiledir.py
浏览文件 @ 17748b7d
......@@ -95,10 +95,10 @@ def cleanup():
def print_title(title, overline="", underline=""):
len_title = len(title)
if overline:
print(str(overline) * len_title)
print(title)
print(str(overline) * len_title) # noqa: T201
print(title) # noqa: T201
if underline:
print(str(underline) * len_title)
print(str(underline) * len_title) # noqa: T201
def print_compiledir_content():
......@@ -159,7 +159,7 @@ def print_compiledir_content():
_logger.error(f"Could not read key file '{filename}'.")
print_title(f"PyTensor cache: {compiledir}", overline="=", underline="=")
print()
print() # noqa: T201
print_title(f"List of {len(table)} compiled individual ops", underline="+")
print_title(
......@@ -168,9 +168,9 @@ def print_compiledir_content():
)
table = sorted(table, key=lambda t: str(t[1]))
for dir, op, types, compile_time in table:
print(dir, f"{compile_time:.3f}s", op, types)
print(dir, f"{compile_time:.3f}s", op, types) # noqa: T201
print()
print() # noqa: T201
print_title(
f"List of {len(table_multiple_ops)} compiled sets of ops", underline="+"
)
......@@ -180,9 +180,9 @@ def print_compiledir_content():
)
table_multiple_ops = sorted(table_multiple_ops, key=lambda t: (t[1], t[2]))
for dir, ops_to_str, types_to_str, compile_time in table_multiple_ops:
print(dir, f"{compile_time:.3f}s", ops_to_str, types_to_str)
print(dir, f"{compile_time:.3f}s", ops_to_str, types_to_str) # noqa: T201
print()
print() # noqa: T201
print_title(
(
f"List of {len(table_op_class)} compiled Op classes and "
......@@ -191,33 +191,33 @@ def print_compiledir_content():
underline="+",
)
for op_class, nb in reversed(table_op_class.most_common()):
print(op_class, nb)
print(op_class, nb) # noqa: T201
if big_key_files:
big_key_files = sorted(big_key_files, key=lambda t: str(t[1]))
big_total_size = sum(sz for _, sz, _ in big_key_files)
print(
print( # noqa: T201
f"There are directories with key files bigger than {int(max_key_file_size)} bytes "
"(they probably contain big tensor constants)"
)
print(
print( # noqa: T201
f"They use {int(big_total_size)} bytes out of {int(total_key_sizes)} (total size "
"used by all key files)"
)
for dir, size, ops in big_key_files:
print(dir, size, ops)
print(dir, size, ops) # noqa: T201
nb_keys = sorted(nb_keys.items())
print()
print() # noqa: T201
print_title("Number of keys for a compiled module", underline="+")
print_title(
"number of keys/number of modules with that number of keys", underline="-"
)
for n_k, n_m in nb_keys:
print(n_k, n_m)
print()
print(
print(n_k, n_m) # noqa: T201
print() # noqa: T201
print( # noqa: T201
f"Skipped {int(zeros_op)} files that contained 0 op "
"(are they always pytensor.scalar ops?)"
)
......@@ -242,18 +242,18 @@ def basecompiledir_ls():
subdirs = sorted(subdirs)
others = sorted(others)
print(f"Base compile dir is {config.base_compiledir}")
print("Sub-directories (possible compile caches):")
print(f"Base compile dir is {config.base_compiledir}") # noqa: T201
print("Sub-directories (possible compile caches):") # noqa: T201
for d in subdirs:
print(f" {d}")
print(f" {d}") # noqa: T201
if not subdirs:
print(" (None)")
print(" (None)") # noqa: T201
if others:
print()
print("Other files in base_compiledir:")
print() # noqa: T201
print("Other files in base_compiledir:") # noqa: T201
for f in others:
print(f" {f}")
print(f" {f}") # noqa: T201
def basecompiledir_purge():
......
pytensor/compile/debugmode.py
浏览文件 @ 17748b7d
......@@ -1315,9 +1315,9 @@ class _VariableEquivalenceTracker:
def printstuff(self):
for key in self.equiv:
print(key)
print(key) # noqa: T201
for e in self.equiv[key]:
print(" ", e)
print(" ", e) # noqa: T201
# List of default version of make thunk.
......@@ -1569,7 +1569,7 @@ class _Linker(LocalLinker):
#####
for r, s in storage_map.items():
if s[0] is not None:
print(r, s)
print(r, s) # noqa: T201
assert s[0] is None
# try:
......@@ -2079,7 +2079,7 @@ class _Maker(FunctionMaker): # inheritance buys a few helper functions
raise StochasticOrder(infolog.getvalue())
else:
if self.verbose:
print(
print( # noqa: T201
"OPTCHECK: optimization",
i,
"of",
......
pytensor/compile/mode.py
浏览文件 @ 17748b7d
......@@ -178,7 +178,7 @@ class PrintCurrentFunctionGraph(GraphRewriter):
def apply(self, fgraph):
import pytensor.printing
print("PrintCurrentFunctionGraph:", self.header)
print("PrintCurrentFunctionGraph:", self.header) # noqa: T201
pytensor.printing.debugprint(fgraph.outputs)
......
pytensor/compile/monitormode.py
浏览文件 @ 17748b7d
......@@ -108,8 +108,8 @@ def detect_nan(fgraph, i, node, fn):
not isinstance(output[0], np.random.RandomState | np.random.Generator)
and np.isnan(output[0]).any()
):
print("*** NaN detected ***")
print("*** NaN detected ***") # noqa: T201
debugprint(node)
print(f"Inputs : {[input[0] for input in fn.inputs]}")
print(f"Outputs: {[output[0] for output in fn.outputs]}")
print(f"Inputs : {[input[0] for input in fn.inputs]}") # noqa: T201
print(f"Outputs: {[output[0] for output in fn.outputs]}") # noqa: T201
break
pytensor/compile/nanguardmode.py
浏览文件 @ 17748b7d
......@@ -236,7 +236,7 @@ class NanGuardMode(Mode):
if config.NanGuardMode__action == "raise":
raise AssertionError(msg)
elif config.NanGuardMode__action == "pdb":
print(msg)
print(msg) # noqa: T201
import pdb
pdb.set_trace()
......
pytensor/compile/profiling.py
浏览文件 @ 17748b7d
......@@ -82,7 +82,7 @@ def _atexit_print_fn():
to_sum.append(ps)
else:
# TODO print the name if there is one!
print("Skipping empty Profile")
print("Skipping empty Profile") # noqa: T201
if len(to_sum) > 1:
# Make a global profile
cum = copy.copy(to_sum[0])
......@@ -125,7 +125,7 @@ def _atexit_print_fn():
assert len(merge) == len(cum.rewriter_profile[1])
cum.rewriter_profile = (cum.rewriter_profile[0], merge)
except Exception as e:
print(e)
print(e) # noqa: T201
cum.rewriter_profile = None
else:
cum.rewriter_profile = None
......
pytensor/graph/features.py
浏览文件 @ 17748b7d
......@@ -491,7 +491,7 @@ class Validator(Feature):
if verbose:
r = uf.f_locals.get("r", "")
reason = uf_info.function
print(f"validate failed on node {r}.\n Reason: {reason}, {e}")
print(f"validate failed on node {r}.\n Reason: {reason}, {e}") # noqa: T201
raise
t1 = time.perf_counter()
if fgraph.profile:
......@@ -603,13 +603,13 @@ class ReplaceValidate(History, Validator):
except Exception as e:
fgraph.revert(chk)
if verbose:
print(
print( # noqa: T201
f"rewriting: validate failed on node {r}.\n Reason: {reason}, {e}"
)
raise
if verbose:
print(
print( # noqa: T201
f"rewriting: rewrite {reason} replaces {r} of {r.owner} with {new_r} of {new_r.owner}"
)
......@@ -692,11 +692,11 @@ class NodeFinder(Bookkeeper):
except TypeError: # node.op is unhashable
return
except Exception as e:
print("OFFENDING node", type(node), type(node.op), file=sys.stderr)
print("OFFENDING node", type(node), type(node.op), file=sys.stderr) # noqa: T201
try:
print("OFFENDING node hash", hash(node.op), file=sys.stderr)
print("OFFENDING node hash", hash(node.op), file=sys.stderr) # noqa: T201
except Exception:
print("OFFENDING node not hashable", file=sys.stderr)
print("OFFENDING node not hashable", file=sys.stderr) # noqa: T201
raise e
def on_prune(self, fgraph, node, reason):
......@@ -725,7 +725,7 @@ class PrintListener(Feature):
def on_attach(self, fgraph):
if self.active:
print("-- attaching to: ", fgraph)
print("-- attaching to: ", fgraph) # noqa: T201
def on_detach(self, fgraph):
"""
......@@ -733,19 +733,19 @@ class PrintListener(Feature):
that it installed into the function_graph
"""
if self.active:
print("-- detaching from: ", fgraph)
print("-- detaching from: ", fgraph) # noqa: T201
def on_import(self, fgraph, node, reason):
if self.active:
print(f"-- importing: {node}, reason: {reason}")
print(f"-- importing: {node}, reason: {reason}") # noqa: T201
def on_prune(self, fgraph, node, reason):
if self.active:
print(f"-- pruning: {node}, reason: {reason}")
print(f"-- pruning: {node}, reason: {reason}") # noqa: T201
def on_change_input(self, fgraph, node, i, r, new_r, reason=None):
if self.active:
print(f"-- changing ({node}.inputs[{i}]) from {r} to {new_r}")
print(f"-- changing ({node}.inputs[{i}]) from {r} to {new_r}") # noqa: T201
class PreserveVariableAttributes(Feature):
......
pytensor/graph/fg.py
浏览文件 @ 17748b7d
......@@ -491,7 +491,7 @@ class FunctionGraph(MetaObject):
if verbose is None:
verbose = config.optimizer_verbose
if verbose:
print(
print( # noqa: T201
f"rewriting: rewrite {reason} replaces {var} of {var.owner} with {new_var} of {new_var.owner}"
)
......
pytensor/graph/rewriting/basic.py
浏览文件 @ 17748b7d
......@@ -1002,7 +1002,7 @@ class MetaNodeRewriter(NodeRewriter):
# ensure we have data for all input variables that need it
if missing:
if self.verbose > 0:
print(
print( # noqa: T201
f"{self.__class__.__name__} cannot meta-rewrite {node}, "
f"{len(missing)} of {int(node.nin)} input shapes unknown"
)
......@@ -1010,7 +1010,7 @@ class MetaNodeRewriter(NodeRewriter):
# now we can apply the different rewrites in turn,
# compile the resulting subgraphs and time their execution
if self.verbose > 1:
print(
print( # noqa: T201
f"{self.__class__.__name__} meta-rewriting {node} ({len(self.get_rewrites(node))} choices):"
)
timings = []
......@@ -1027,20 +1027,20 @@ class MetaNodeRewriter(NodeRewriter):
continue
except Exception as e:
if self.verbose > 0:
print(f"* {node_rewriter}: exception", e)
print(f"* {node_rewriter}: exception", e) # noqa: T201
continue
else:
if self.verbose > 1:
print(f"* {node_rewriter}: {timing:.5g} sec")
print(f"* {node_rewriter}: {timing:.5g} sec") # noqa: T201
timings.append((timing, outputs, node_rewriter))
else:
if self.verbose > 0:
print(f"* {node_rewriter}: not applicable")
print(f"* {node_rewriter}: not applicable") # noqa: T201
# finally, we choose the fastest one
if timings:
timings.sort()
if self.verbose > 1:
print(f"= {timings[0][2]}")
print(f"= {timings[0][2]}") # noqa: T201
return timings[0][1]
return
......@@ -1305,7 +1305,7 @@ class SequentialNodeRewriter(NodeRewriter):
new_vars = list(new_repl.values())
if config.optimizer_verbose:
print(
print( # noqa: T201
f"rewriting: rewrite {rewrite} replaces node {node} with {new_repl}"
)
......@@ -2641,21 +2641,21 @@ class EquilibriumGraphRewriter(NodeProcessingGraphRewriter):
try:
o.print_profile(stream, prof, level + 2)
except NotImplementedError:
print(blanc, "merge not implemented for ", o)
print(blanc, "merge not implemented for ", o) # noqa: T201
for o, prof in zip(
rewrite.final_rewriters, final_sub_profs[i], strict=True
):
try:
o.print_profile(stream, prof, level + 2)
except NotImplementedError:
print(blanc, "merge not implemented for ", o)
print(blanc, "merge not implemented for ", o) # noqa: T201
for o, prof in zip(
rewrite.cleanup_rewriters, cleanup_sub_profs[i], strict=True
):
try:
o.print_profile(stream, prof, level + 2)
except NotImplementedError:
print(blanc, "merge not implemented for ", o)
print(blanc, "merge not implemented for ", o) # noqa: T201
@staticmethod
def merge_profile(prof1, prof2):
......
pytensor/graph/utils.py
浏览文件 @ 17748b7d
......@@ -274,9 +274,9 @@ class Scratchpad:
return "scratchpad" + str(self.__dict__)
def info(self):
print(f"<pytensor.graph.utils.scratchpad instance at {id(self)}>")
print(f"<pytensor.graph.utils.scratchpad instance at {id(self)}>") # noqa: T201
for k, v in self.__dict__.items():
print(f" {k}: {v}")
print(f" {k}: {v}") # noqa: T201
# These two methods have been added to help Mypy
def __getattribute__(self, name):
......
pytensor/link/c/basic.py
浏览文件 @ 17748b7d
......@@ -875,10 +875,10 @@ class CLinker(Linker):
self.c_init_code_apply = c_init_code_apply
if (self.init_tasks, self.tasks) != self.get_init_tasks():
print("init_tasks\n", self.init_tasks, file=sys.stderr)
print(self.get_init_tasks()[0], file=sys.stderr)
print("tasks\n", self.tasks, file=sys.stderr)
print(self.get_init_tasks()[1], file=sys.stderr)
print("init_tasks\n", self.init_tasks, file=sys.stderr) # noqa: T201
print(self.get_init_tasks()[0], file=sys.stderr) # noqa: T201
print("tasks\n", self.tasks, file=sys.stderr) # noqa: T201
print(self.get_init_tasks()[1], file=sys.stderr) # noqa: T201
assert (self.init_tasks, self.tasks) == self.get_init_tasks()
# List of indices that should be ignored when passing the arguments
......@@ -1756,7 +1756,7 @@ class _CThunk:
exc_value = exc_type(_exc_value)
exc_value.__thunk_trace__ = trace
except Exception:
print(
print( # noqa: T201
(
"ERROR retrieving error_storage."
"Was the error set in the c code?"
......@@ -1764,7 +1764,7 @@ class _CThunk:
end=" ",
file=sys.stderr,
)
print(self.error_storage, file=sys.stderr)
print(self.error_storage, file=sys.stderr) # noqa: T201
raise
raise exc_value.with_traceback(exc_trace)
......
pytensor/link/c/op.py
浏览文件 @ 17748b7d
......@@ -79,7 +79,7 @@ class COp(Op, CLinkerOp):
# that don't implement c code. In those cases, we
# don't want to print a warning.
cl.get_dynamic_module()
print(f"Disabling C code for {self} due to unsupported float16")
warnings.warn(f"Disabling C code for {self} due to unsupported float16")
raise NotImplementedError("float16")
outputs = cl.make_thunk(
input_storage=node_input_storage, output_storage=node_output_storage
......
pytensor/printing.py
浏览文件 @ 17748b7d
......@@ -726,7 +726,7 @@ def _print_fn(op, xin):
pmsg = temp()
else:
pmsg = temp
print(op.message, attr, "=", pmsg)
print(op.message, attr, "=", pmsg) # noqa: T201
class Print(Op):
......@@ -1657,7 +1657,7 @@ def pydotprint(
raise
if print_output_file:
print("The output file is available at", outfile)
print("The output file is available at", outfile) # noqa: T201
class _TagGenerator:
......@@ -1824,8 +1824,7 @@ def var_descriptor(obj, _prev_obs: dict | None = None, _tag_generator=None) -> s
# The __str__ method is encoding the object's id in its str
name = position_independent_str(obj)
if " at 0x" in name:
print(name)
raise AssertionError()
raise AssertionError(name)
prefix = cur_tag + "="
......
pytensor/tensor/basic.py
浏览文件 @ 17748b7d
......@@ -613,7 +613,6 @@ def get_scalar_constant_value(
"""
if isinstance(v, TensorVariable | np.ndarray):
if v.ndim != 0:
print(v, v.ndim)
raise NotScalarConstantError("Input ndim != 0")
return get_underlying_scalar_constant_value(
v,
......
pytensor/tensor/nlinalg.py
浏览文件 @ 17748b7d
......@@ -216,9 +216,8 @@ class Det(Op):
(z,) = outputs
try:
z[0] = np.asarray(np.linalg.det(x), dtype=x.dtype)
except Exception:
print("Failed to compute determinant", x)
raise
except Exception as e:
raise ValueError("Failed to compute determinant", x) from e
def grad(self, inputs, g_outputs):
(gz,) = g_outputs
......@@ -256,9 +255,8 @@ class SLogDet(Op):
(sign, det) = outputs
try:
sign[0], det[0] = (np.array(z, dtype=x.dtype) for z in np.linalg.slogdet(x))
except Exception:
print("Failed to compute determinant", x)
raise
except Exception as e:
raise ValueError("Failed to compute determinant", x) from e
def infer_shape(self, fgraph, node, shapes):
return [(), ()]
......
pytensor/tensor/rewriting/blas.py
浏览文件 @ 17748b7d
......@@ -573,7 +573,7 @@ class GemmOptimizer(GraphRewriter):
print(blanc, " callbacks_time", file=stream)
for i in sorted(prof[12].items(), key=lambda a: a[1]):
if i[1] > 0:
print(i)
print(i) # noqa: T201
@node_rewriter([Dot])
......
pytensor/tensor/rewriting/elemwise.py
浏览文件 @ 17748b7d
......@@ -314,14 +314,14 @@ class InplaceElemwiseOptimizer(GraphRewriter):
except (ValueError, InconsistencyError) as e:
prof["nb_inconsistent"] += 1
if check_each_change != 1 and not raised_warning:
print(
print( # noqa: T201
(
"Some inplace rewriting was not "
"performed due to an unexpected error:"
),
file=sys.stderr,
)
print(e, file=sys.stderr)
print(e, file=sys.stderr) # noqa: T201
raised_warning = True
fgraph.revert(chk)
continue
......@@ -335,7 +335,7 @@ class InplaceElemwiseOptimizer(GraphRewriter):
fgraph.validate()
except Exception:
if not raised_warning:
print(
print( # noqa: T201
(
"Some inplace rewriting was not "
"performed due to an unexpected error"
......@@ -1080,7 +1080,7 @@ class FusionOptimizer(GraphRewriter):
print(blanc, " callbacks_time", file=stream)
for i in sorted(prof[6].items(), key=lambda a: a[1])[::-1]:
if i[1] > 0:
print(blanc, " ", i)
print(blanc, " ", i) # noqa: T201
print(blanc, " time_toposort", prof[7], file=stream)
......
pytensor/tensor/rewriting/math.py
浏览文件 @ 17748b7d
......@@ -3434,14 +3434,14 @@ def perform_sigm_times_exp(
sigm_minus_x = []
if full_tree is None:
full_tree = tree
if False: # Debug code.
print("<perform_sigm_times_exp>")
print(f" full_tree = {full_tree}")
print(f" tree = {tree}")
print(f" exp_x = {exp_x}")
print(f" exp_minus_x = {exp_minus_x}")
print(f" sigm_x = {sigm_x}")
print(f" sigm_minus_x= {sigm_minus_x}")
# if False: # Debug code.
# print("<perform_sigm_times_exp>")
# print(f" full_tree = {full_tree}")
# print(f" tree = {tree}")
# print(f" exp_x = {exp_x}")
# print(f" exp_minus_x = {exp_minus_x}")
# print(f" sigm_x = {sigm_x}")
# print(f" sigm_minus_x= {sigm_minus_x}")
neg, inputs = tree
if isinstance(inputs, list):
# Recurse through inputs of the multiplication.
......
scripts/slowest_tests/extract-slow-tests.py
浏览文件 @ 17748b7d
......@@ -72,7 +72,7 @@ def main(read_lines):
lines = read_lines()
times = extract_lines(lines)
parsed_times = format_times(times)
print("\n".join(parsed_times))
print("\n".join(parsed_times)) # noqa: T201
if __name__ == "__main__":
......
tests/d3viz/test_d3viz.py
浏览文件 @ 17748b7d
......@@ -28,7 +28,7 @@ class TestD3Viz:
tmp_dir = Path(tempfile.mkdtemp())
html_file = tmp_dir / "index.html"
if verbose:
print(html_file)
print(html_file) # noqa: T201
d3v.d3viz(f, html_file)
assert html_file.stat().st_size > 0
if reference:
......
tests/link/c/test_cmodule.py
浏览文件 @ 17748b7d
......@@ -258,7 +258,6 @@ def test_default_blas_ldflags(
def patched_compile_tmp(*args, **kwargs):
def wrapped(test_code, tmp_prefix, flags, try_run, output):
if len(flags) >= 2 and flags[:2] == ["-framework", "Accelerate"]:
print(enabled_accelerate_framework)
if enabled_accelerate_framework:
return (True, True)
else:
......
tests/link/numba/test_basic.py
浏览文件 @ 17748b7d
......@@ -836,7 +836,6 @@ def test_config_options_fastmath():
with config.change_flags(numba__fastmath=True):
pytensor_numba_fn = function([x], pt.sum(x), mode=numba_mode)
print(list(pytensor_numba_fn.vm.jit_fn.py_func.__globals__))
numba_mul_fn = pytensor_numba_fn.vm.jit_fn.py_func.__globals__["impl_sum"]
assert numba_mul_fn.targetoptions["fastmath"] == {
"afn",
......
tests/link/test_vm.py
浏览文件 @ 17748b7d
import time
from collections import Counter
import numpy as np
......@@ -108,23 +107,25 @@ def test_speed():
return z
def time_numpy():
# TODO: Make this a benchmark test
steps_a = 5
steps_b = 100
x = np.asarray([2.0, 3.0], dtype=config.floatX)
numpy_version(x, steps_a)
t0 = time.perf_counter()
# print numpy_version(x, steps_a)
t1 = time.perf_counter()
t2 = time.perf_counter()
# print numpy_version(x, steps_b)
t3 = time.perf_counter()
t_a = t1 - t0
t_b = t3 - t2
# t0 = time.perf_counter()
numpy_version(x, steps_a)
# t1 = time.perf_counter()
# t2 = time.perf_counter()
numpy_version(x, steps_b)
# t3 = time.perf_counter()
# t_a = t1 - t0
# t_b = t3 - t2
print(f"numpy takes {1000 * (t_b - t_a) / (steps_b - steps_a):f} s/Kop")
# print(f"numpy takes {1000 * (t_b - t_a) / (steps_b - steps_a):f} s/Kop")
def time_linker(name, linker):
# TODO: Make this a benchmark test
steps_a = 5
steps_b = 100
x = vector()
......@@ -135,20 +136,20 @@ def test_speed():
f_b = function([x], b, mode=Mode(optimizer=None, linker=linker()))
f_a([2.0, 3.0])
t0 = time.perf_counter()
# t0 = time.perf_counter()
f_a([2.0, 3.0])
t1 = time.perf_counter()
# t1 = time.perf_counter()
f_b([2.0, 3.0])
t2 = time.perf_counter()
# t2 = time.perf_counter()
f_b([2.0, 3.0])
t3 = time.perf_counter()
# t3 = time.perf_counter()
t_a = t1 - t0
t_b = t3 - t2
# t_a = t1 - t0
# t_b = t3 - t2
print(f"{name} takes {1000 * (t_b - t_a) / (steps_b - steps_a):f} s/Kop")
# print(f"{name} takes {1000 * (t_b - t_a) / (steps_b - steps_a):f} s/Kop")
time_linker("c|py", OpWiseCLinker)
time_linker("vmLinker", VMLinker)
......@@ -167,7 +168,7 @@ def test_speed():
],
)
def test_speed_lazy(linker):
# TODO FIXME: This isn't a real test.
# TODO FIXME: This isn't a real test. Make this a benchmark test
def build_graph(x, depth=5):
z = x
......@@ -185,20 +186,20 @@ def test_speed_lazy(linker):
f_b = function([x], b, mode=Mode(optimizer=None, linker=linker))
f_a([2.0])
t0 = time.perf_counter()
# t0 = time.perf_counter()
f_a([2.0])
t1 = time.perf_counter()
# t1 = time.perf_counter()
f_b([2.0])
t2 = time.perf_counter()
# t2 = time.perf_counter()
f_b([2.0])
t3 = time.perf_counter()
# t3 = time.perf_counter()
t_a = t1 - t0
t_b = t3 - t2
# t_a = t1 - t0
# t_b = t3 - t2
print(f"{linker} takes {1000 * (t_b - t_a) / (steps_b - steps_a):f} s/Kop")
# print(f"{linker} takes {1000 * (t_b - t_a) / (steps_b - steps_a):f} s/Kop")
@pytest.mark.parametrize(
......
tests/scan/test_basic.py
浏览文件 @ 17748b7d
......@@ -12,7 +12,6 @@ Questions and notes about scan that should be answered :
import os
import pickle
import shutil
import sys
from pathlib import Path
from tempfile import mkdtemp
......@@ -3076,7 +3075,7 @@ class TestExamples:
cost = result_outer[0][-1]
H = hessian(cost, W)
print(".", file=sys.stderr)
# print(".", file=sys.stderr)
f = function([W, n_steps], H)
benchmark(f, np.ones((8,), dtype="float32"), 1)
......
tests/tensor/rewriting/test_math.py
浏览文件 @ 17748b7d
......@@ -1628,6 +1628,7 @@ def test_local_mul_specialize():
def speed_local_pow_specialize_range():
# TODO: This should be a benchmark test
val = np.random.random(1e7)
v = vector()
mode = get_default_mode()
......@@ -1641,9 +1642,9 @@ def speed_local_pow_specialize_range():
t2 = time.perf_counter()
f2(val)
t3 = time.perf_counter()
print(i, t2 - t1, t3 - t2, t2 - t1 < t3 - t2)
# print(i, t2 - t1, t3 - t2, t2 - t1 < t3 - t2)
if not t2 - t1 < t3 - t2:
print("WARNING WE ARE SLOWER")
raise ValueError("WARNING WE ARE SLOWER")
for i in range(-3, -1500, -1):
f1 = function([v], v**i, mode=mode)
f2 = function([v], v**i, mode=mode_without_pow_rewrite)
......@@ -1653,9 +1654,9 @@ def speed_local_pow_specialize_range():
t2 = time.perf_counter()
f2(val)
t3 = time.perf_counter()
print(i, t2 - t1, t3 - t2, t2 - t1 < t3 - t2)
# print(i, t2 - t1, t3 - t2, t2 - t1 < t3 - t2)
if not t2 - t1 < t3 - t2:
print("WARNING WE ARE SLOWER")
raise ValueError("WARNING WE ARE SLOWER")
def test_local_pow_specialize():
......@@ -2483,19 +2484,20 @@ class TestLocalErfc:
assert f.maker.fgraph.outputs[0].dtype == config.floatX
def speed_local_log_erfc(self):
# TODO: Make this a benchmark test!
val = np.random.random(1e6)
x = vector()
mode = get_mode("FAST_RUN")
f1 = function([x], log(erfc(x)), mode=mode.excluding("local_log_erfc"))
f2 = function([x], log(erfc(x)), mode=mode)
print(f1.maker.fgraph.toposort())
print(f2.maker.fgraph.toposort())
t0 = time.perf_counter()
# print(f1.maker.fgraph.toposort())
# print(f2.maker.fgraph.toposort())
# t0 = time.perf_counter()
f1(val)
t1 = time.perf_counter()
# t1 = time.perf_counter()
f2(val)
t2 = time.perf_counter()
print(t1 - t0, t2 - t1)
# t2 = time.perf_counter()
# print(t1 - t0, t2 - t1)
class TestLocalMergeSwitchSameCond:
......@@ -4144,13 +4146,13 @@ class TestSigmoidRewrites:
perform_sigm_times_exp(trees[0])
trees[0] = simplify_mul(trees[0])
good = is_same_graph(compute_mul(trees[0]), compute_mul(trees[1]))
if not good:
print(trees[0])
print(trees[1])
print("***")
pytensor.printing.debugprint(compute_mul(trees[0]))
print("***")
pytensor.printing.debugprint(compute_mul(trees[1]))
# if not good:
# print(trees[0])
# print(trees[1])
# print("***")
# pytensor.printing.debugprint(compute_mul(trees[0]))
# print("***")
# pytensor.printing.debugprint(compute_mul(trees[1]))
assert good
check(sigmoid(x) * exp_op(-x), sigmoid(-x))
......
tests/tensor/test_complex.py
浏览文件 @ 17748b7d
......@@ -73,9 +73,7 @@ class TestRealImag:
try:
utt.verify_grad(f, [aval])
except GradientError as e:
print(e.num_grad.gf)
print(e.analytic_grad)
raise
raise ValueError(f"Failed: {e.num_grad.gf=} {e.analytic_grad=}") from e
@pytest.mark.skip(reason="Complex grads not enabled, see #178")
def test_mul_mixed1(self):
......@@ -88,9 +86,7 @@ class TestRealImag:
try:
utt.verify_grad(f, [aval])
except GradientError as e:
print(e.num_grad.gf)
print(e.analytic_grad)
raise
raise ValueError(f"Failed: {e.num_grad.gf=} {e.analytic_grad=}") from e
@pytest.mark.skip(reason="Complex grads not enabled, see #178")
def test_mul_mixed(self):
......@@ -104,9 +100,7 @@ class TestRealImag:
try:
utt.verify_grad(f, [aval, bval])
except GradientError as e:
print(e.num_grad.gf)
print(e.analytic_grad)
raise
raise ValueError(f"Failed: {e.num_grad.gf=} {e.analytic_grad=}") from e
@pytest.mark.skip(reason="Complex grads not enabled, see #178")
def test_polar_grads(self):
......
tests/tensor/test_fft.py
浏览文件 @ 17748b7d
......@@ -43,7 +43,6 @@ class TestFFT:
utt.assert_allclose(rfft_ref, res_rfft_comp)
m = rfft.type()
print(m.ndim)
irfft = fft.irfft(m)
f_irfft = pytensor.function([m], irfft)
res_irfft = f_irfft(res_rfft)
......
tests/tensor/test_shape.py
浏览文件 @ 17748b7d
......@@ -797,7 +797,6 @@ class TestVectorize:
assert equal_computations([vect_out], [reshape(mat, new_shape)])
new_shape = stack([[-1, x], [x - 1, -1]], axis=0)
print(new_shape.type)
[vect_out] = vectorize_node(node, vec, new_shape).outputs
vec_test_value = np.arange(6)
np.testing.assert_allclose(
......
tests/test_config.py
浏览文件 @ 17748b7d
......@@ -192,7 +192,7 @@ def test_invalid_configvar_access():
# But we can make sure that nothing crazy happens when we access it:
with pytest.raises(configparser.ConfigAccessViolation, match="different instance"):
print(root.test__on_test_instance)
assert root.test__on_test_instance is not None
def test_no_more_dotting():
......
tests/test_printing.py
浏览文件 @ 17748b7d
......@@ -138,9 +138,9 @@ def test_min_informative_str():
D. D
E. E"""
if mis != reference:
print("--" + mis + "--")
print("--" + reference + "--")
# if mis != reference:
# print("--" + mis + "--")
# print("--" + reference + "--")
assert mis == reference
......
tests/unittest_tools.py
浏览文件 @ 17748b7d
import logging
import sys
import warnings
from copy import copy, deepcopy
from functools import wraps
......@@ -41,12 +42,9 @@ def fetch_seed(pseed=None):
else:
seed = None
except ValueError:
print(
(
"Error: config.unittests__rseed contains "
"invalid seed, using None instead"
),
file=sys.stderr,
warnings.warn(
"Error: config.unittests__rseed contains "
"invalid seed, using None instead"
)
seed = None
......
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