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[Cleanup][A-1,A-2,A-3,A-4] clean some VarType for test #61466

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Feb 3, 2024
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[Cleanup][A-1,A-2,A-3,A-4] clean some VarType for test #61466

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3b5353e
clean some VarType for test
ooooo-create Feb 2, 2024
9a1edc9
fix
ooooo-create Feb 2, 2024
ae82e62
fix
ooooo-create Feb 3, 2024
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13 changes: 6 additions & 7 deletions test/auto_parallel/amp_o2_pass.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,6 @@

import paddle
from paddle.distributed.fleet import auto
from paddle.framework import core

paddle.enable_static()

Expand Down Expand Up @@ -98,11 +97,11 @@ def check_bf16(self, program):
num_fp32 = 0

for p in program.all_parameters():
if p.dtype == core.VarDesc.VarType.FP32:
if p.dtype == paddle.float32:
num_fp32 += 1
if p.dtype == core.VarDesc.VarType.FP16:
if p.dtype == paddle.float16:
num_fp16 += 1
if p.dtype == core.VarDesc.VarType.BF16:
if p.dtype == paddle.bfloat16:
num_bf16 += 1

self.assertEqual(num_bf16, 26)
Expand All @@ -115,11 +114,11 @@ def check_fp16(self, program):
num_fp32 = 0

for p in program.all_parameters():
if p.dtype == core.VarDesc.VarType.FP32:
if p.dtype == paddle.float32:
num_fp32 += 1
if p.dtype == core.VarDesc.VarType.FP16:
if p.dtype == paddle.float16:
num_fp16 += 1
if p.dtype == core.VarDesc.VarType.BF16:
if p.dtype == paddle.bfloat16:
num_bf16 += 1

self.assertEqual(num_bf16, 0)
Expand Down
19 changes: 6 additions & 13 deletions test/auto_parallel/test_pass_bf16.py
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Original file line number Diff line number Diff line change
Expand Up @@ -19,7 +19,6 @@

import paddle
from paddle import nn
from paddle.base import core
from paddle.distributed.fleet import auto
from paddle.static import InputSpec
from paddle.static.amp.bf16.amp_utils import _valid_types
Expand Down Expand Up @@ -139,7 +138,7 @@ def check_program(self, program):
break

if op.type in bf16_op_list:
assert var.dtype == core.VarDesc.VarType.BF16
assert var.dtype == paddle.bfloat16
if "cast_bf16" in in_var_name:
if "@GRAD" in in_var_name:
tmp_in_var_name = in_var_name[
Expand All @@ -155,18 +154,15 @@ def check_program(self, program):
for in_name in prev_op.input_names:
for in_var_name in prev_op.input(in_name):
var = block.var(in_var_name)
assert (
var.dtype
== core.VarDesc.VarType.FP32
)
assert var.dtype == paddle.float32

elif op.type in fp32_op_list:
if (
op.type == "softmax_with_cross_entropy"
or op.type == "softmax_with_cross_entropy_grad"
) and in_var_name == "label0":
continue
assert var.dtype == core.VarDesc.VarType.FP32
assert var.dtype == paddle.float32
if "cast_fp32" in in_var_name:
prev_op = find_true_prev_op(
block.ops, op, tmp_in_var_name
Expand All @@ -176,10 +172,7 @@ def check_program(self, program):
for in_name in prev_op.input_names:
for in_var_name in prev_op.input(in_name):
var = block.var(in_var_name)
assert (
var.dtype
== core.VarDesc.VarType.BF16
)
assert var.dtype == paddle.bfloat16

for out_name in op.output_names:
for out_var_name in op.output(out_name):
Expand All @@ -192,9 +185,9 @@ def check_program(self, program):
if var is None or var.type not in _valid_types:
break
if op.type in bf16_op_list:
assert var.dtype == core.VarDesc.VarType.BF16
assert var.dtype == paddle.bfloat16
elif op.type in fp32_op_list:
assert var.dtype == core.VarDesc.VarType.FP32
assert var.dtype == paddle.float32

def test_bf16_pass(self):
bf16_o1_engine = self.get_engine(True)
Expand Down
26 changes: 11 additions & 15 deletions test/collective/fleet/test_imperative_auto_mixed_precision_for_eager.py
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Original file line number Diff line number Diff line change
Expand Up @@ -65,9 +65,9 @@ def amp_guard_white_op(self):
with paddle.amp.amp_guard(False):
out_fp32 = conv2d(data)

self.assertTrue(data.dtype == base.core.VarDesc.VarType.FP32)
self.assertTrue(out_fp16.dtype == base.core.VarDesc.VarType.FP16)
self.assertTrue(out_fp32.dtype == base.core.VarDesc.VarType.FP32)
self.assertTrue(data.dtype == paddle.float32)
self.assertTrue(out_fp16.dtype == paddle.float16)
self.assertTrue(out_fp32.dtype == paddle.float32)

def test_amp_guard_white_op(self):
self.amp_guard_white_op()
Expand All @@ -79,8 +79,8 @@ def amp_guard_black_op(self):
with paddle.amp.amp_guard(True):
out_fp32 = paddle.mean(data)

self.assertTrue(data.dtype == base.core.VarDesc.VarType.FP32)
self.assertTrue(out_fp32.dtype == base.core.VarDesc.VarType.FP32)
self.assertTrue(data.dtype == paddle.float32)
self.assertTrue(out_fp32.dtype == paddle.float32)

def test_amp_guard_black_op(self):
self.amp_guard_black_op()
Expand Down Expand Up @@ -164,15 +164,11 @@ def amp_guard_upsupported_fp16_op(self):
out_purefp16_fp32 = paddle.expand_as(
out_purefp16_fp16, out_purefp16_fp16
) # expand_as_v2 has no fp16 kernel
self.assertTrue(data.dtype == base.core.VarDesc.VarType.FP32)
self.assertTrue(out_amp_fp16.dtype == base.core.VarDesc.VarType.FP16)
self.assertTrue(out_amp_fp32.dtype == base.core.VarDesc.VarType.FP32)
self.assertTrue(
out_purefp16_fp16.dtype == base.core.VarDesc.VarType.FP16
)
self.assertTrue(
out_purefp16_fp32.dtype == base.core.VarDesc.VarType.FP32
)
self.assertTrue(data.dtype == paddle.float32)
self.assertTrue(out_amp_fp16.dtype == paddle.float16)
self.assertTrue(out_amp_fp32.dtype == paddle.float32)
self.assertTrue(out_purefp16_fp16.dtype == paddle.float16)
self.assertTrue(out_purefp16_fp32.dtype == paddle.float32)

def test_amp_guard_upsupported_fp16_op(self):
self.amp_guard_upsupported_fp16_op()
Expand Down Expand Up @@ -1357,7 +1353,7 @@ def func_isinstance():
with paddle.amp.auto_cast(custom_white_list=['layer_norm']):
out = layer_norm(x)

self.assertTrue(out.dtype == base.core.VarDesc.VarType.FP16)
self.assertTrue(out.dtype == paddle.float16)

func_isinstance()

Expand Down
5 changes: 1 addition & 4 deletions test/custom_op/test_custom_conj.py
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Original file line number Diff line number Diff line change
Expand Up @@ -41,10 +41,7 @@


def is_complex(dtype):
return (
dtype == paddle.base.core.VarDesc.VarType.COMPLEX64
or dtype == paddle.base.core.VarDesc.VarType.COMPLEX128
)
return dtype == paddle.complex64 or dtype == paddle.complex128


def to_complex(dtype):
Expand Down
8 changes: 2 additions & 6 deletions test/dygraph_to_static/test_to_tensor.py
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Expand Up @@ -223,17 +223,13 @@ def test_static(self):
if paddle.base.framework.use_pir_api():
self.assertTrue(x.dtype == paddle.base.libpaddle.DataType.INT16)
else:
self.assertTrue(
x.dtype == paddle.framework.core.VarDesc.VarType.INT16
)
self.assertTrue(x.dtype == paddle.int16)

y = paddle.to_tensor([1, 2], dtype="int16")
if paddle.base.framework.use_pir_api():
self.assertTrue(y.dtype == paddle.base.libpaddle.DataType.INT16)
else:
self.assertTrue(
y.dtype == paddle.framework.core.VarDesc.VarType.INT16
)
self.assertTrue(y.dtype == paddle.int16)


if __name__ == '__main__':
Expand Down
6 changes: 3 additions & 3 deletions test/ir/test_ir_fusion_group_pass.py
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Expand Up @@ -65,11 +65,11 @@ def _feed_random_data(self, feed_vars):
raise TypeError("Feed data of non LoDTensor is not supported.")

shape = var.shape
if var.dtype == base.core.VarDesc.VarType.FP32:
if var.dtype == paddle.float32:
dtype = "float32"
elif var.dtype == base.core.VarDesc.VarType.FP64:
elif var.dtype == paddle.float64:
dtype = "float64"
elif var.dtype == base.core.VarDesc.VarType.FP16:
elif var.dtype == paddle.float16:
dtype = "float16"
else:
raise ValueError("Unsupported dtype %s" % var.dtype)
Expand Down
6 changes: 3 additions & 3 deletions test/legacy_test/gradient_checker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -31,11 +31,11 @@ def _product(t):


def dtype_to_np_dtype(dtype):
if dtype == core.VarDesc.VarType.FP32 or dtype == core.DataType.FLOAT32:
if dtype == paddle.float32 or dtype == core.DataType.FLOAT32:
return np.float32
elif dtype == core.VarDesc.VarType.FP64 or dtype == core.DataType.FLOAT64:
elif dtype == paddle.float64 or dtype == core.DataType.FLOAT64:
return np.float64
elif dtype == core.VarDesc.VarType.FP16 or dtype == core.DataType.FLOAT16:
elif dtype == paddle.float16 or dtype == core.DataType.FLOAT16:
return np.float16
else:
raise ValueError("Not supported data type " + str(dtype))
Expand Down
20 changes: 10 additions & 10 deletions test/legacy_test/op_test.py
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Expand Up @@ -166,19 +166,19 @@ def product(dim):
tensor_to_check = scope.find_var(input_to_check).get_tensor()
tensor_size = product(tensor_to_check.shape())
tensor_to_check_dtype = tensor_to_check._dtype()
if tensor_to_check_dtype == core.VarDesc.VarType.FP32:
if tensor_to_check_dtype == paddle.float32:
tensor_to_check_dtype = np.float32
elif tensor_to_check_dtype == core.VarDesc.VarType.FP64:
elif tensor_to_check_dtype == paddle.float64:
tensor_to_check_dtype = np.float64
elif tensor_to_check_dtype == core.VarDesc.VarType.FP16:
elif tensor_to_check_dtype == paddle.float16:
tensor_to_check_dtype = np.float16
# set delta as np.float16, will automatic convert to float32, float64
delta = np.array(delta).astype(np.float16)
elif tensor_to_check_dtype == core.VarDesc.VarType.BF16:
elif tensor_to_check_dtype == paddle.bfloat16:
tensor_to_check_dtype = np.float32
elif tensor_to_check_dtype == core.VarDesc.VarType.COMPLEX64:
elif tensor_to_check_dtype == paddle.complex64:
tensor_to_check_dtype = np.complex64
elif tensor_to_check_dtype == core.VarDesc.VarType.COMPLEX128:
elif tensor_to_check_dtype == paddle.complex128:
tensor_to_check_dtype = np.complex128
else:
raise ValueError(
Expand All @@ -196,7 +196,7 @@ def get_output():
# numpy.dtype does not have bfloat16, thus we use numpy.uint16 to
# store bfloat16 data, and need to be converted to float to check
# the floating precision.
if tensor_to_check._dtype() == core.VarDesc.VarType.BF16:
if tensor_to_check._dtype() == paddle.bfloat16:
output_numpy = convert_uint16_to_float(output_numpy)
sum.append(output_numpy.astype(tensor_to_check_dtype).mean())
return tensor_to_check_dtype(np.array(sum).sum() / len(output_names))
Expand All @@ -208,7 +208,7 @@ def __get_elem__(tensor, i):
numpy_tensor = np.array(tensor).astype(np.float16)
numpy_tensor = numpy_tensor.flatten()
return numpy_tensor[i]
elif tensor_to_check._dtype() == core.VarDesc.VarType.BF16:
elif tensor_to_check._dtype() == paddle.bfloat16:
numpy_tensor = np.array(tensor).astype(np.uint16)
numpy_tensor = numpy_tensor.flatten()
return struct.unpack(
Expand Down Expand Up @@ -236,7 +236,7 @@ def __set_elem__(tensor, i, e):
numpy_tensor[i] = e
numpy_tensor = numpy_tensor.reshape(shape)
tensor.set(numpy_tensor, place)
elif tensor_to_check._dtype() == core.VarDesc.VarType.BF16:
elif tensor_to_check._dtype() == paddle.bfloat16:
numpy_tensor = np.array(tensor).astype(np.uint16)
shape = numpy_tensor.shape
numpy_tensor = numpy_tensor.flatten()
Expand Down Expand Up @@ -3470,7 +3470,7 @@ def _get_dygraph_grad(
for cast_input in cast_inputs:
if isinstance(cast_input, paddle.Tensor):
cast_outputs.append(
paddle.cast(cast_input, core.VarDesc.VarType.FP32)
paddle.cast(cast_input, paddle.float32)
)
else:
raise TypeError(
Expand Down
4 changes: 2 additions & 2 deletions test/legacy_test/test_batch_norm_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -203,9 +203,9 @@ def __set_tensor__(name, data=None):
grad_tensor = scope.var(grad_var_name(name)).get_tensor()
out_dtype = out_tensor.dtype()
if data is None:
if out_dtype == core.VarDesc.VarType.FP64:
if out_dtype == paddle.float64:
data = np.ones(out_tensor.shape(), dtype=np.float64)
elif out_dtype == core.VarDesc.VarType.FP32:
elif out_dtype == paddle.float32:
data = np.ones(out_tensor.shape(), dtype=np.float32)
else:
raise ValueError("Not supported data type " + str(out_dtype))
Expand Down
3 changes: 1 addition & 2 deletions test/legacy_test/test_cummax_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,6 @@

import paddle
from paddle import base
from paddle.base import core
from paddle.pir_utils import test_with_pir_api


Expand Down Expand Up @@ -143,7 +142,7 @@ def run_cases(self):
z, ind = cummax_dim2(data_np, axis=-2)
np.testing.assert_array_equal(z, y.numpy())
np.testing.assert_array_equal(ind, indices.numpy())
self.assertTrue(indices.dtype == core.VarDesc.VarType.INT32)
self.assertTrue(indices.dtype == paddle.int32)

data_np = np.random.randint(0, 10, size=(100, 100)).astype(np.int32)
data = paddle.to_tensor(data_np)
Expand Down
3 changes: 1 addition & 2 deletions test/legacy_test/test_cummin_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -20,7 +20,6 @@

import paddle
from paddle import base
from paddle.base import core
from paddle.pir_utils import test_with_pir_api


Expand Down Expand Up @@ -143,7 +142,7 @@ def run_cases(self):
z, ind = cummin_dim2(data_np, axis=-2)
np.testing.assert_array_equal(z, y.numpy())
np.testing.assert_array_equal(ind, indices.numpy())
self.assertTrue(indices.dtype == core.VarDesc.VarType.INT32)
self.assertTrue(indices.dtype == paddle.int32)

data_np = np.random.randint(0, 10, size=(100, 100)).astype(np.int32)
data = paddle.to_tensor(data_np)
Expand Down
4 changes: 2 additions & 2 deletions test/legacy_test/test_cumsum_op.py
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Expand Up @@ -44,10 +44,10 @@ def run_cases(self):
np.testing.assert_array_equal(z, y.numpy())

y = paddle.cumsum(data, dtype='float64')
self.assertTrue(y.dtype == core.VarDesc.VarType.FP64)
self.assertTrue(y.dtype == paddle.float64)

y = paddle.cumsum(data, dtype=np.int32)
self.assertTrue(y.dtype == core.VarDesc.VarType.INT32)
self.assertTrue(y.dtype == paddle.int32)

y = paddle.cumsum(data, axis=-2)
z = np.cumsum(data_np, axis=-2)
Expand Down
8 changes: 4 additions & 4 deletions test/legacy_test/test_elementwise_add_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -776,7 +776,7 @@ def test_static_add(self):
a = 1.5
b = paddle.full([4, 5, 6], True, dtype='bool')
c = a + b
self.assertTrue(c.dtype == core.VarDesc.VarType.FP32)
self.assertTrue(c.dtype == paddle.float32)
with paddle.pir_utils.IrGuard():
a = 1.5
b = paddle.full([4, 5, 6], True, dtype='bool')
Expand All @@ -789,7 +789,7 @@ def test_dygraph_add(self):
b = paddle.full([2], True, dtype='bool')
# special case: scalar + tensor(bool)
c = a + b
self.assertTrue(c.dtype == core.VarDesc.VarType.FP32)
self.assertTrue(c.dtype == paddle.float32)

np_a = np.random.random((2, 3, 4)).astype(np.float64)
np_b = np.random.random((2, 3, 4)).astype(np.float64)
Expand Down Expand Up @@ -843,7 +843,7 @@ def test_float32_add(self):
a = paddle.full([4, 5, 6], 1.5, dtype='float32')
b = np.array([1.5], dtype='float32')[0]
c = a + b
self.assertTrue(c.dtype == core.VarDesc.VarType.FP32)
self.assertTrue(c.dtype == paddle.float32)

def test_float16_add(self):
if not core.is_compiled_with_cuda():
Expand All @@ -852,7 +852,7 @@ def test_float16_add(self):
a = paddle.full([4, 5, 6], 1.5, dtype='float16')
b = np.array([1.5], dtype='float16')[0]
c = a + b
self.assertTrue(c.dtype == core.VarDesc.VarType.FP16)
self.assertTrue(c.dtype == paddle.float16)


class TestTensorAddAPIWarnings(unittest.TestCase):
Expand Down
3 changes: 1 addition & 2 deletions test/legacy_test/test_gather_op.py
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Expand Up @@ -616,8 +616,7 @@ def test_out_type(self):
index = paddle.static.data(shape=[4], dtype='int64', name='index')
out = paddle.gather(data, index)
self.assertTrue(
out.dtype == core.VarDesc.VarType.INT64
or out.dtype == core.DataType.INT64
out.dtype == paddle.int64 or out.dtype == core.DataType.INT64
)

def test_pir_out_type(self):
Expand Down
2 changes: 1 addition & 1 deletion test/legacy_test/test_logcumsumexp_op.py
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Expand Up @@ -122,7 +122,7 @@ def run_imperative(self):
np.testing.assert_allclose(z, y.numpy(), rtol=1e-05)

y = paddle.logcumsumexp(data, dtype='float32')
self.assertTrue(y.dtype == core.VarDesc.VarType.FP32)
self.assertTrue(y.dtype == paddle.float32)

y = paddle.logcumsumexp(data, axis=-2)
z = np_logcumsumexp(data_np, axis=-2)
Expand Down