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提交 1a530729 authored 作者: Brandon T. Willard's avatar Brandon T. Willard 提交者： Brandon T. Willard
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Simplify TensorType.shape format in str output

上级 b3a69117
隐藏空白字符变更
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正在显示 包含 79 行增加 和 60 行删除
aesara/tensor/type.py
浏览文件 @ 1a530729
......@@ -386,7 +386,18 @@ class TensorType(CType[np.ndarray], HasDataType, HasShape):
if self.name:
return self.name
else:
return f"TensorType({self.dtype}, {self.shape})"
def shape_str(s):
if s is None:
return "?"
else:
return str(s)
formatted_shape = ", ".join([shape_str(s) for s in self.shape])
if len(self.shape) == 1:
formatted_shape += ","
return f"TensorType({self.dtype}, ({formatted_shape}))"
def __repr__(self):
return str(self)
......
doc/extending/graphstructures.rst
浏览文件 @ 1a530729
......@@ -217,7 +217,7 @@ For example, :ref:`aesara.tensor.irow <libdoc_tensor_creation>` is an instance o
>>> from aesara.tensor import irow
>>> irow()
<TensorType(int32, (1, None))>
<TensorType(int32, (1, ?))>
As the string print-out shows, `irow` specifies the following information about
the :class:`Variable`\s it constructs:
......
doc/extending/type.rst
浏览文件 @ 1a530729
......@@ -90,7 +90,7 @@ For example, let's say we have two :class:`Variable`\s with the following
>>> from aesara.tensor.type import TensorType
>>> v1 = TensorType("float64", (2, None))()
>>> v1.type
TensorType(float64, (2, None))
TensorType(float64, (2, ?))
>>> v2 = TensorType("float64", (2, 1))()
>>> v2.type
TensorType(float64, (2, 1))
......@@ -145,7 +145,7 @@ SpecifyShape.0
>>> import aesara
>>> aesara.dprint(v3, print_type=True)
SpecifyShape [id A] <TensorType(float64, (2, 1))>
|<TensorType(float64, (2, None))> [id B] <TensorType(float64, (2, None))>
|<TensorType(float64, (2, ?))> [id B] <TensorType(float64, (2, ?))>
|TensorConstant{2} [id C] <TensorType(int8, ())>
|TensorConstant{1} [id D] <TensorType(int8, ())>
......
doc/library/scan.rst
浏览文件 @ 1a530729
......@@ -406,7 +406,7 @@ Using the original Gibbs sampling example, with ``strict=True`` added to the
Traceback (most recent call last):
...
MissingInputError: An input of the graph, used to compute
DimShuffle{1,0}(<TensorType(float64, (None, None))>), was not provided and
DimShuffle{1,0}(<TensorType(float64, (?, ?))>), was not provided and
not given a value.Use the Aesara flag exception_verbosity='high',for
more information on this error.
......
doc/tutorial/debug_faq.rst
浏览文件 @ 1a530729
......@@ -44,8 +44,8 @@ Running the code above we see:
Traceback (most recent call last):
...
ValueError: Input dimension mismatch. (input[0].shape[0] = 3, input[1].shape[0] = 2)
Apply node that caused the error: Elemwise{add,no_inplace}(<TensorType(float64, (None,))>, <TensorType(float64, (None,))>, <TensorType(float64, (None,))>)
Inputs types: [TensorType(float64, (None,)), TensorType(float64, (None,)), TensorType(float64, (None,))]
Apply node that caused the error: Elemwise{add,no_inplace}(<TensorType(float64, (?,))>, <TensorType(float64, (?,))>, <TensorType(float64, (?,))>)
Inputs types: [TensorType(float64, (?,)), TensorType(float64, (?,)), TensorType(float64, (?,))]
Inputs shapes: [(3,), (2,), (2,)]
Inputs strides: [(8,), (8,), (8,)]
Inputs scalar values: ['not scalar', 'not scalar', 'not scalar']
......@@ -73,11 +73,11 @@ message becomes :
z = z + y
Debugprint of the apply node:
Elemwise{add,no_inplace} [id A] <TensorType(float64, (None,))> ''
|Elemwise{add,no_inplace} [id B] <TensorType(float64, (None,))> ''
| |<TensorType(float64, (None,))> [id C] <TensorType(float64, (None,))>
| |<TensorType(float64, (None,))> [id C] <TensorType(float64, (None,))>
|<TensorType(float64, (None,))> [id D] <TensorType(float64, (None,))>
Elemwise{add,no_inplace} [id A] <TensorType(float64, (?,))> ''
|Elemwise{add,no_inplace} [id B] <TensorType(float64, (?,))> ''
| |<TensorType(float64, (?,))> [id C] <TensorType(float64, (?,))>
| |<TensorType(float64, (?,))> [id C] <TensorType(float64, (?,))>
|<TensorType(float64, (?,))> [id D] <TensorType(float64, (?,))>
We can here see that the error can be traced back to the line ``z = z + y``.
For this example, using ``optimizer=fast_compile`` worked. If it did not,
......@@ -145,18 +145,18 @@ Running the above code generates the following error message:
outputs = self.vm()
ValueError: Shape mismatch: x has 10 cols (and 5 rows) but y has 20 rows (and 10 cols)
Apply node that caused the error: Dot22(x, DimShuffle{1,0}.0)
Inputs types: [TensorType(float64, (None, None)), TensorType(float64, (None, None))]
Inputs types: [TensorType(float64, (?, ?)), TensorType(float64, (?, ?))]
Inputs shapes: [(5, 10), (20, 10)]
Inputs strides: [(80, 8), (8, 160)]
Inputs scalar values: ['not scalar', 'not scalar']
Debugprint of the apply node:
Dot22 [id A] <TensorType(float64, (None, None))> ''
|x [id B] <TensorType(float64, (None, None))>
|DimShuffle{1,0} [id C] <TensorType(float64, (None, None))> ''
|Flatten{2} [id D] <TensorType(float64, (None, None))> ''
|DimShuffle{2,0,1} [id E] <TensorType(float64, (None, None, None))> ''
|W1 [id F] <TensorType(float64, (None, None, None))>
Dot22 [id A] <TensorType(float64, (?, ?))> ''
|x [id B] <TensorType(float64, (?, ?))>
|DimShuffle{1,0} [id C] <TensorType(float64, (?, ?))> ''
|Flatten{2} [id D] <TensorType(float64, (?, ?))> ''
|DimShuffle{2,0,1} [id E] <TensorType(float64, (?, ?, ?))> ''
|W1 [id F] <TensorType(float64, (?, ?, ?))>
HINT: Re-running with most Aesara optimization disabled could give you a back-traces when this node was created. This can be done with by setting the Aesara flags 'optimizer=fast_compile'. If that does not work, Aesara optimization can be disabled with 'optimizer=None'.
......@@ -483,7 +483,7 @@ Consider this example script (``ex.py``):
ValueError: Input dimension mismatch. (input[0].shape[0] = 3, input[1].shape[0] = 5)
Apply node that caused the error: Elemwise{mul,no_inplace}(a, b)
Toposort index: 0
Inputs types: [TensorType(float64, (None, None)), TensorType(float64, (None, None))]
Inputs types: [TensorType(float64, (?, ?)), TensorType(float64, (?, ?))]
Inputs shapes: [(3, 4), (5, 5)]
Inputs strides: [(32, 8), (40, 8)]
Inputs values: ['not shown', 'not shown']
......
tests/compile/test_builders.py
浏览文件 @ 1a530729
......@@ -580,10 +580,10 @@ Inner graphs:
OpFromGraph{inline=False} [id A]
>Elemwise{add,no_inplace} [id E]
> |*0-<TensorType(float64, (None, None))> [id F]
> |*0-<TensorType(float64, (?, ?))> [id F]
> |Elemwise{mul,no_inplace} [id G]
> |*1-<TensorType(float64, (None, None))> [id H]
> |*2-<TensorType(float64, (None, None))> [id I]
> |*1-<TensorType(float64, (?, ?))> [id H]
> |*2-<TensorType(float64, (?, ?))> [id I]
"""
for truth, out in zip(exp_res.split("\n"), lines):
......
tests/scan/test_printing.py
浏览文件 @ 1a530729
......@@ -58,8 +58,8 @@ def test_debugprint_sitsot():
for{cpu,scan_fn} [id C] (outer_out_sit_sot-0)
>Elemwise{mul,no_inplace} [id W] (inner_out_sit_sot-0)
> |*0-<TensorType(float64, (None,))> [id X] -> [id E] (inner_in_sit_sot-0)
> |*1-<TensorType(float64, (None,))> [id Y] -> [id M] (inner_in_non_seqs-0)"""
> |*0-<TensorType(float64, (?,))> [id X] -> [id E] (inner_in_sit_sot-0)
> |*1-<TensorType(float64, (?,))> [id Y] -> [id M] (inner_in_non_seqs-0)"""
for truth, out in zip(expected_output.split("\n"), lines):
assert truth.strip() == out.strip()
......@@ -113,8 +113,8 @@ def test_debugprint_sitsot_no_extra_info():
for{cpu,scan_fn} [id C]
>Elemwise{mul,no_inplace} [id W]
> |*0-<TensorType(float64, (None,))> [id X] -> [id E]
> |*1-<TensorType(float64, (None,))> [id Y] -> [id M]"""
> |*0-<TensorType(float64, (?,))> [id X] -> [id E]
> |*1-<TensorType(float64, (?,))> [id Y] -> [id M]"""
for truth, out in zip(expected_output.split("\n"), lines):
assert truth.strip() == out.strip()
......@@ -264,7 +264,7 @@ def test_debugprint_nested_scans():
> | | | | | | | |Unbroadcast{0} [id BL]
> | | | | | | | |InplaceDimShuffle{x,0} [id BM]
> | | | | | | | |Elemwise{second,no_inplace} [id BN]
> | | | | | | | |*2-<TensorType(float64, (None,))> [id BO] -> [id W] (inner_in_non_seqs-0)
> | | | | | | | |*2-<TensorType(float64, (?,))> [id BO] -> [id W] (inner_in_non_seqs-0)
> | | | | | | | |InplaceDimShuffle{x} [id BP]
> | | | | | | | |TensorConstant{1.0} [id BQ]
> | | | | | | |ScalarConstant{0} [id BR]
......@@ -275,7 +275,7 @@ def test_debugprint_nested_scans():
> | | | | |Unbroadcast{0} [id BL]
> | | | | |ScalarFromTensor [id BV]
> | | | | |Subtensor{int64} [id BJ]
> | | | |*2-<TensorType(float64, (None,))> [id BO] -> [id W] (inner_in_non_seqs-0) (outer_in_non_seqs-0)
> | | | |*2-<TensorType(float64, (?,))> [id BO] -> [id W] (inner_in_non_seqs-0) (outer_in_non_seqs-0)
> | | |ScalarConstant{1} [id BW]
> | |ScalarConstant{-1} [id BX]
> |InplaceDimShuffle{x} [id BY]
......@@ -283,8 +283,8 @@ def test_debugprint_nested_scans():
for{cpu,scan_fn} [id BE] (outer_out_sit_sot-0)
>Elemwise{mul,no_inplace} [id CA] (inner_out_sit_sot-0)
> |*0-<TensorType(float64, (None,))> [id CB] -> [id BG] (inner_in_sit_sot-0)
> |*1-<TensorType(float64, (None,))> [id CC] -> [id BO] (inner_in_non_seqs-0)"""
> |*0-<TensorType(float64, (?,))> [id CB] -> [id BG] (inner_in_sit_sot-0)
> |*1-<TensorType(float64, (?,))> [id CC] -> [id BO] (inner_in_non_seqs-0)"""
for truth, out in zip(expected_output.split("\n"), lines):
assert truth.strip() == out.strip()
......@@ -334,7 +334,7 @@ def test_debugprint_nested_scans():
for{cpu,scan_fn} [id E] (outer_out_nit_sot-0)
-*0-<TensorType(float64, ())> [id Y] -> [id U] (inner_in_seqs-0)
-*1-<TensorType(int64, ())> [id Z] -> [id W] (inner_in_seqs-1)
-*2-<TensorType(float64, (None,))> [id BA] -> [id C] (inner_in_non_seqs-0)
-*2-<TensorType(float64, (?,))> [id BA] -> [id C] (inner_in_non_seqs-0)
-*3-<TensorType(int32, ())> [id BB] -> [id B] (inner_in_non_seqs-1)
>Elemwise{mul,no_inplace} [id BC] (inner_out_nit_sot-0)
> |InplaceDimShuffle{x} [id BD]
......@@ -353,7 +353,7 @@ def test_debugprint_nested_scans():
> | | | | | | | |Unbroadcast{0} [id BN]
> | | | | | | | |InplaceDimShuffle{x,0} [id BO]
> | | | | | | | |Elemwise{second,no_inplace} [id BP]
> | | | | | | | |*2-<TensorType(float64, (None,))> [id BA] (inner_in_non_seqs-0)
> | | | | | | | |*2-<TensorType(float64, (?,))> [id BA] (inner_in_non_seqs-0)
> | | | | | | | |InplaceDimShuffle{x} [id BQ]
> | | | | | | | |TensorConstant{1.0} [id BR]
> | | | | | | |ScalarConstant{0} [id BS]
......@@ -364,18 +364,18 @@ def test_debugprint_nested_scans():
> | | | | |Unbroadcast{0} [id BN]
> | | | | |ScalarFromTensor [id BW]
> | | | | |Subtensor{int64} [id BL]
> | | | |*2-<TensorType(float64, (None,))> [id BA] (inner_in_non_seqs-0) (outer_in_non_seqs-0)
> | | | |*2-<TensorType(float64, (?,))> [id BA] (inner_in_non_seqs-0) (outer_in_non_seqs-0)
> | | |ScalarConstant{1} [id BX]
> | |ScalarConstant{-1} [id BY]
> |InplaceDimShuffle{x} [id BZ]
> |*1-<TensorType(int64, ())> [id Z] (inner_in_seqs-1)
for{cpu,scan_fn} [id BH] (outer_out_sit_sot-0)
-*0-<TensorType(float64, (None,))> [id CA] -> [id BI] (inner_in_sit_sot-0)
-*1-<TensorType(float64, (None,))> [id CB] -> [id BA] (inner_in_non_seqs-0)
-*0-<TensorType(float64, (?,))> [id CA] -> [id BI] (inner_in_sit_sot-0)
-*1-<TensorType(float64, (?,))> [id CB] -> [id BA] (inner_in_non_seqs-0)
>Elemwise{mul,no_inplace} [id CC] (inner_out_sit_sot-0)
> |*0-<TensorType(float64, (None,))> [id CA] (inner_in_sit_sot-0)
> |*1-<TensorType(float64, (None,))> [id CB] (inner_in_non_seqs-0)"""
> |*0-<TensorType(float64, (?,))> [id CA] (inner_in_sit_sot-0)
> |*1-<TensorType(float64, (?,))> [id CB] (inner_in_non_seqs-0)"""
for truth, out in zip(expected_output.split("\n"), lines):
assert truth.strip() == out.strip()
......@@ -413,7 +413,7 @@ def test_debugprint_mitsot():
| | | | |Subtensor{int64} [id H]
| | | | |Shape [id I]
| | | | | |Subtensor{:int64:} [id J]
| | | | | |<TensorType(int64, (None,))> [id K]
| | | | | |<TensorType(int64, (?,))> [id K]
| | | | | |ScalarConstant{2} [id L]
| | | | |ScalarConstant{0} [id M]
| | | |Subtensor{:int64:} [id J]
......@@ -426,7 +426,7 @@ def test_debugprint_mitsot():
| | | |Subtensor{int64} [id R]
| | | |Shape [id S]
| | | | |Subtensor{:int64:} [id T]
| | | | |<TensorType(int64, (None,))> [id U]
| | | | |<TensorType(int64, (?,))> [id U]
| | | | |ScalarConstant{2} [id V]
| | | |ScalarConstant{0} [id W]
| | |Subtensor{:int64:} [id T]
......@@ -562,19 +562,19 @@ def test_debugprint_mitmot():
for{cpu,grad_of_scan_fn}.1 [id B] (outer_out_sit_sot-0)
>Elemwise{add,no_inplace} [id CM] (inner_out_mit_mot-0-0)
> |Elemwise{mul} [id CN]
> | |*2-<TensorType(float64, (None,))> [id CO] -> [id BL] (inner_in_mit_mot-0-0)
> | |*5-<TensorType(float64, (None,))> [id CP] -> [id P] (inner_in_non_seqs-0)
> |*3-<TensorType(float64, (None,))> [id CQ] -> [id BL] (inner_in_mit_mot-0-1)
> | |*2-<TensorType(float64, (?,))> [id CO] -> [id BL] (inner_in_mit_mot-0-0)
> | |*5-<TensorType(float64, (?,))> [id CP] -> [id P] (inner_in_non_seqs-0)
> |*3-<TensorType(float64, (?,))> [id CQ] -> [id BL] (inner_in_mit_mot-0-1)
>Elemwise{add,no_inplace} [id CR] (inner_out_sit_sot-0)
> |Elemwise{mul} [id CS]
> | |*2-<TensorType(float64, (None,))> [id CO] -> [id BL] (inner_in_mit_mot-0-0)
> | |*0-<TensorType(float64, (None,))> [id CT] -> [id Z] (inner_in_seqs-0)
> |*4-<TensorType(float64, (None,))> [id CU] -> [id CE] (inner_in_sit_sot-0)
> | |*2-<TensorType(float64, (?,))> [id CO] -> [id BL] (inner_in_mit_mot-0-0)
> | |*0-<TensorType(float64, (?,))> [id CT] -> [id Z] (inner_in_seqs-0)
> |*4-<TensorType(float64, (?,))> [id CU] -> [id CE] (inner_in_sit_sot-0)
for{cpu,scan_fn} [id F] (outer_out_sit_sot-0)
>Elemwise{mul,no_inplace} [id CV] (inner_out_sit_sot-0)
> |*0-<TensorType(float64, (None,))> [id CT] -> [id H] (inner_in_sit_sot-0)
> |*1-<TensorType(float64, (None,))> [id CW] -> [id P] (inner_in_non_seqs-0)"""
> |*0-<TensorType(float64, (?,))> [id CT] -> [id H] (inner_in_sit_sot-0)
> |*1-<TensorType(float64, (?,))> [id CW] -> [id P] (inner_in_non_seqs-0)"""
for truth, out in zip(expected_output.split("\n"), lines):
assert truth.strip() == out.strip()
......
tests/tensor/rewriting/test_basic.py
浏览文件 @ 1a530729
......@@ -614,8 +614,8 @@ class TestUselessElemwise:
f2 = function([x], eq(x, x), mode=self.mode)
assert np.all(f2(vx) == np.ones((5, 4)))
topo2 = f2.maker.fgraph.toposort()
# Shape_i{1}(<TensorType(float64, (None, None))>),
# Shape_i{0}(<TensorType(float64, (None, None))>), Alloc([[1]], Shape_i{0}.0,
# Shape_i{1}(<TensorType(float64, (?, ?))>),
# Shape_i{0}(<TensorType(float64, (?, ?))>), Alloc([[1]], Shape_i{0}.0,
# Shape_i{1}.0
assert len(topo2) == 3
assert isinstance(topo2[-1].op, Alloc)
......
tests/tensor/rewriting/test_elemwise.py
浏览文件 @ 1a530729
......@@ -82,6 +82,7 @@ class TestDimshuffleLift:
x, y, z = inputs()
e = ds(ds(x, (1, 0)), (1, 0))
g = FunctionGraph([x], [e])
# TODO FIXME: Construct these graphs and compare them.
assert (
str(g) == "FunctionGraph(InplaceDimShuffle{1,0}(InplaceDimShuffle{1,0}(x)))"
)
......@@ -93,6 +94,7 @@ class TestDimshuffleLift:
x, y, z = inputs()
e = ds(ds(x, (1, "x", 0)), (2, 0, "x", 1))
g = FunctionGraph([x], [e])
# TODO FIXME: Construct these graphs and compare them.
assert (
str(g)
== "FunctionGraph(InplaceDimShuffle{2,0,x,1}(InplaceDimShuffle{1,x,0}(x)))"
......@@ -106,6 +108,7 @@ class TestDimshuffleLift:
x, y, z = inputs()
e = ds(ds(ds(x, (0, "x", 1)), (2, 0, "x", 1)), (1, 0))
g = FunctionGraph([x], [e])
# TODO FIXME: Construct these graphs and compare them.
assert str(g) == (
"FunctionGraph(InplaceDimShuffle{1,0}(InplaceDimShuffle{2,0,x,1}"
"(InplaceDimShuffle{0,x,1}(x))))"
......@@ -119,6 +122,7 @@ class TestDimshuffleLift:
e = x + y + z
g = FunctionGraph([x, y, z], [e])
# TODO FIXME: Construct these graphs and compare them.
# It does not really matter if the DimShuffles are inplace
# or not.
init_str_g_inplace = (
......@@ -149,13 +153,14 @@ class TestDimshuffleLift:
m = matrix(dtype="float64")
out = ((v + 42) * (m + 84)).T
g = FunctionGraph([v, m], [out])
# TODO FIXME: Construct these graphs and compare them.
init_str_g = (
"FunctionGraph(InplaceDimShuffle{1,0}(Elemwise{mul,no_inplace}"
"(InplaceDimShuffle{x,0}(Elemwise{add,no_inplace}"
"(<TensorType(float64, (None,))>, "
"(<TensorType(float64, (?,))>, "
"InplaceDimShuffle{x}(TensorConstant{42}))), "
"Elemwise{add,no_inplace}"
"(<TensorType(float64, (None, None))>, "
"(<TensorType(float64, (?, ?))>, "
"InplaceDimShuffle{x,x}(TensorConstant{84})))))"
)
assert str(g) == init_str_g
......@@ -163,10 +168,10 @@ class TestDimshuffleLift:
new_g = FunctionGraph(g.inputs, [new_out])
rewrite_str_g = (
"FunctionGraph(Elemwise{mul,no_inplace}(Elemwise{add,no_inplace}"
"(InplaceDimShuffle{0,x}(<TensorType(float64, (None,))>), "
"(InplaceDimShuffle{0,x}(<TensorType(float64, (?,))>), "
"InplaceDimShuffle{x,x}(TensorConstant{42})), "
"Elemwise{add,no_inplace}(InplaceDimShuffle{1,0}"
"(<TensorType(float64, (None, None))>), "
"(<TensorType(float64, (?, ?))>), "
"InplaceDimShuffle{x,x}(TensorConstant{84}))))"
)
assert str(new_g) == rewrite_str_g
......@@ -177,6 +182,7 @@ class TestDimshuffleLift:
x, _, _ = inputs()
e = ds(x, (0, 1))
g = FunctionGraph([x], [e])
# TODO FIXME: Construct these graphs and compare them.
assert str(g) == "FunctionGraph(InplaceDimShuffle{0,1}(x))"
dimshuffle_lift.rewrite(g)
assert str(g) == "FunctionGraph(x)"
......@@ -191,6 +197,7 @@ class TestDimshuffleLift:
ds_z = ds(z, (2, 1, 0)) # useful
ds_u = ds(u, ("x")) # useful
g = FunctionGraph([x, y, z, u], [ds_x, ds_y, ds_z, ds_u])
# TODO FIXME: Construct these graphs and compare them.
assert (
str(g)
== "FunctionGraph(InplaceDimShuffle{0,x}(x), InplaceDimShuffle{2,1,0}(y), InplaceDimShuffle{2,1,0}(z), InplaceDimShuffle{x}(TensorConstant{1}))"
......@@ -225,6 +232,7 @@ def test_local_useless_dimshuffle_in_reshape():
],
)
# TODO FIXME: Construct these graphs and compare them.
assert str(g) == (
"FunctionGraph(Reshape{1}(InplaceDimShuffle{x,0}(vector), Shape(vector)), "
"Reshape{2}(InplaceDimShuffle{x,0,x,1}(mat), Shape(mat)), "
......
tests/tensor/test_sharedvar.py
浏览文件 @ 1a530729
......@@ -513,7 +513,7 @@ def makeSharedTester(
)
topo = f.maker.fgraph.toposort()
f()
# [Gemm{inplace}(<TensorType(float64, (None, None))>, 0.01, <TensorType(float64, (None, None))>, <TensorType(float64, (None, None))>, 2e-06)]
# [Gemm{inplace}(<TensorType(float64, (?, ?))>, 0.01, <TensorType(float64, (?, ?))>, <TensorType(float64, (?, ?))>, 2e-06)]
if aesara.config.mode != "FAST_COMPILE":
assert (
sum(
......
tests/test_printing.py
浏览文件 @ 1a530729
......@@ -282,7 +282,7 @@ def test_debugprint():
| | |B
| |TensorConstant{1.0}
| |B
| |<TensorType(float64, (None,))>
| |<TensorType(float64, (?,))>
| |TensorConstant{0.0}
|D
"""
......@@ -306,9 +306,9 @@ def test_debugprint_id_type():
exp_res = f"""Elemwise{{add,no_inplace}} [id {e_at.auto_name}]
|dot [id {d_at.auto_name}]
| |<TensorType(float64, (None, None))> [id {b_at.auto_name}]
| |<TensorType(float64, (None,))> [id {a_at.auto_name}]
|<TensorType(float64, (None,))> [id {a_at.auto_name}]
| |<TensorType(float64, (?, ?))> [id {b_at.auto_name}]
| |<TensorType(float64, (?,))> [id {a_at.auto_name}]
|<TensorType(float64, (?,))> [id {a_at.auto_name}]
"""
assert [l.strip() for l in s.split("\n")] == [
......@@ -319,7 +319,7 @@ def test_debugprint_id_type():
def test_pprint():
x = dvector()
y = x[1]
assert pp(y) == "<TensorType(float64, (None,))>[1]"
assert pp(y) == "<TensorType(float64, (?,))>[1]"
def test_debugprint_inner_graph():
......
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