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Merged
merged 2 commits into from
Feb 25, 2025
Merged

Fix typos in test directory #66981

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3434af7
Fix
co63oc Feb 23, 2025
c97931e
Merge branch 'develop' into fix_send_v2
co63oc Feb 24, 2025
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6 changes: 3 additions & 3 deletions test/collective/README.md
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Expand Up @@ -7,14 +7,14 @@
the properties are the following:
* `name`: the test's name
* `os`: The supported operator system, ignoring case. If the test run in multiple operator systems, use ";" to split systems, for example, `apple;linux` means the test runs on both Apple and Linux. The supported values are `linux`,`win32` and `apple`. If the value is empty, this means the test runs on all operator systems.
* `arch`: the device's architecture. similar to `os`, multiple values are splited by ";" and ignoring case. The supported architectures are `gpu`, `xpu` and `rocm`.
* `arch`: the device's architecture. similar to `os`, multiple values are split by ";" and ignoring case. The supported architectures are `gpu`, `xpu` and `rocm`.
* `timeout`: timeout of a unittest, whose unit is second. Blank means default.
* `run_type`: run_type of a unittest. Supported values are `NIGHTLY`, `EXCLUSIVE`, `CINN`, `DIST`, `GPUPS`, `INFER`, `EXCLUSIVE:NIGHTLY`, `DIST:NIGHTLY`，which are case-insensitive.
* `launcher`: the test launcher.Supported values are test_runner.py, dist_test.sh and custom scripts' name. Blank means test_runner.py.
* `num_port`: the number of port used in a distributed unit test. Blank means automatically distributed port.
* `run_serial`: whether in serial mode. the value can be 1 or 0.Default (empty) is 0. Blank means default.
* `ENVS`: required environments. multiple environments are splited by ";".
* `conditions`: extra required conditions for some tests. The value is a list of boolean expression in cmake programmer, splited with ";". For example, the value can be `WITH_DGC;NOT WITH_NCCL` or `WITH_NCCL;${NCCL_VERSION} VERSION_GREATER_EQUAL 2212`,The relationship between these expressions is a conjunction.
* `ENVS`: required environments. multiple environments are split by ";".
* `conditions`: extra required conditions for some tests. The value is a list of boolean expression in cmake programmer, split with ";". For example, the value can be `WITH_DGC;NOT WITH_NCCL` or `WITH_NCCL;${NCCL_VERSION} VERSION_GREATER_EQUAL 2212`,The relationship between these expressions is a conjunction.

### step 3. Generate CMakeLists.txt
Run the cmd:
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4 changes: 2 additions & 2 deletions test/deprecated/legacy_test/test_group_norm_op_deprecated.py
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Expand Up @@ -1529,7 +1529,7 @@ def get_static_desire(self, place):
if core._is_fwd_prim_enabled():
paddle.incubate.autograd.primapi.to_prim(mp.blocks)
fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that group_norm is splitted into small ops
# Ensure that group_norm is split into small ops
assert 'group_norm' not in fwd_ops_new

grads = paddle.static.gradients([output], [input_, scale_, bias_])
Expand Down Expand Up @@ -1621,7 +1621,7 @@ def test_static_comp(self):
if core._is_fwd_prim_enabled():
paddle.incubate.autograd.primapi.to_prim(mp.blocks)
fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that group_norm is splitted into small ops
# Ensure that group_norm is split into small ops
assert 'group_norm' not in fwd_ops_new

grads = paddle.static.gradients(
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4 changes: 2 additions & 2 deletions test/deprecated/legacy_test/test_instance_norm_op_deprecated.py
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Expand Up @@ -502,7 +502,7 @@ def get_static_desire(self, place):
if core._is_fwd_prim_enabled():
paddle.incubate.autograd.primapi.to_prim(mp.blocks)
fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that instance_norm is splitted into small ops
# Ensure that instance_norm is split into small ops
assert 'instance_norm' not in fwd_ops_new

grads = paddle.static.gradients([output], [input_, scale_, bias_])
Expand Down Expand Up @@ -586,7 +586,7 @@ def test_static_comp(self):
if core._is_fwd_prim_enabled():
paddle.incubate.autograd.primapi.to_prim(mp.blocks)
fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that instance_norm is splitted into small ops
# Ensure that instance_norm is split into small ops
assert 'instance_norm' not in fwd_ops_new

grads = paddle.static.gradients(
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2 changes: 1 addition & 1 deletion test/deprecated/prim/composite_ops/test_composite_batch_norm_deprecated.py
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Expand Up @@ -207,7 +207,7 @@ def cal_static(inputs, running_mean, running_variance, weight, bias, mode=None):
if mode:
primapi.to_prim(blocks)
fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that batch_norm is splitted into small ops
# Ensure that batch_norm is split into small ops
assert (
'batch_norm' not in fwd_ops_new
and 'reduce_mean' not in fwd_ops_new
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2 changes: 1 addition & 1 deletion test/deprecated/prim/composite_ops/test_composite_gelu_deprecated.py
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Expand Up @@ -90,7 +90,7 @@ def cal_composite(self, inputs):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that gelu is splitted into small ops
# Ensure that gelu is split into small ops
self.assertTrue('gelu' not in fwd_ops_new)

exe = paddle.static.Executor()
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2 changes: 1 addition & 1 deletion test/deprecated/prim/composite_ops/test_composite_gelu_grad_deprecated.py
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Expand Up @@ -98,7 +98,7 @@ def cal_composite_grad(self, inputs):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that gelu is splitted into small ops
# Ensure that gelu is split into small ops
self.assertTrue('gelu' not in fwd_ops_new)

z = paddle.static.gradients([y], x)
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4 changes: 2 additions & 2 deletions test/deprecated/prim/composite_ops/test_composite_layer_norm_deprecated.py
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Expand Up @@ -166,7 +166,7 @@ def cal_composite(self, inputs, norm_shape, weight, bias):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that layer_norm is splitted into small ops
# Ensure that layer_norm is split into small ops
self.assertTrue('layer_norm' not in fwd_ops_new)

exe = paddle.static.Executor()
Expand Down Expand Up @@ -205,7 +205,7 @@ def cal2_composite(self, inputs, norm_shape, weight, bias):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that layer_norm is splitted into small ops
# Ensure that layer_norm is split into small ops
self.assertTrue('layer_norm' not in fwd_ops_new)

exe = paddle.static.Executor()
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6 changes: 3 additions & 3 deletions test/deprecated/prim/composite_ops/test_composite_layer_norm_grad_deprecated.py
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Expand Up @@ -222,7 +222,7 @@ def static_comp_forward(self, inputs, norm_shape, weight, bias, y_g):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that layer_norm is splitted into small ops
# Ensure that layer_norm is split into small ops
self.assertTrue('layer_norm' not in fwd_ops_new)

z = paddle.static.gradients([y], [x, w, b], y_grad)
Expand Down Expand Up @@ -273,7 +273,7 @@ def static_comp_forward_withNone(
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that layer_norm is splitted into small ops
# Ensure that layer_norm is split into small ops
self.assertTrue('layer_norm' not in fwd_ops_new)

z = paddle.static.gradients([y], x, y_grad)
Expand Down Expand Up @@ -663,7 +663,7 @@ def static_comp_forward(self, inputs, norm_shape, weight, bias, y_grad):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that layer_norm is splitted into small ops
# Ensure that layer_norm is split into small ops
self.assertTrue('layer_norm' not in fwd_ops_new)

z = paddle.static.gradients([y], x, y_g)
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2 changes: 1 addition & 1 deletion test/deprecated/prim/composite_ops/test_composite_mean_deprecated.py
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Expand Up @@ -93,7 +93,7 @@ def cal_composite(self, inputs):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that reduce_mean is splitted into small ops
# Ensure that reduce_mean is split into small ops
self.assertTrue('reduce_mean' not in fwd_ops_new)

exe = paddle.static.Executor()
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2 changes: 1 addition & 1 deletion test/deprecated/prim/composite_ops/test_composite_mean_grad_deprecated.py
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Expand Up @@ -99,7 +99,7 @@ def cal_composite_grad(self, inputs):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that reduce_mean is splitted into small ops
# Ensure that reduce_mean is split into small ops
self.assertTrue('reduce_mean' not in fwd_ops_new)

z = paddle.static.gradients([y], x)
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2 changes: 1 addition & 1 deletion test/deprecated/prim/composite_ops/test_composite_softmax_custom_vjp_deprecated.py
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Expand Up @@ -93,7 +93,7 @@ def cal_composite_grad(self, inputs):
paddle.incubate.autograd.primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that softmax is splitted into small ops
# Ensure that softmax is split into small ops
self.assertTrue('softmax' not in fwd_ops_new)

z = paddle.static.gradients([y], x)
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2 changes: 1 addition & 1 deletion test/deprecated/prim/composite_ops/test_composite_softmax_deprecated.py
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Expand Up @@ -88,7 +88,7 @@ def cal_composite(self, inputs):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that softmax is splitted into small ops
# Ensure that softmax is split into small ops
self.assertTrue('softmax' not in fwd_ops_new)

exe = paddle.static.Executor()
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2 changes: 1 addition & 1 deletion test/deprecated/prim/composite_ops/test_composite_softmax_grad_deprecated.py
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Expand Up @@ -94,7 +94,7 @@ def cal_composite_grad(self, inputs):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that softmax is splitted into small ops
# Ensure that softmax is split into small ops
self.assertTrue('softmax' not in fwd_ops_new)

z = paddle.static.gradients([y], x)
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4 changes: 2 additions & 2 deletions test/deprecated/prim/prim/flags/test_prim_flags_deprecated.py
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Expand Up @@ -93,7 +93,7 @@ def not_in_blacklist(self):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that softmax is splitted into small ops
# Ensure that softmax is split into small ops
self.assertTrue('softmax' not in fwd_ops_new)

exe = paddle.static.Executor()
Expand Down Expand Up @@ -122,7 +122,7 @@ def in_blacklist(self):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that softmax is splitted into small ops
# Ensure that softmax is split into small ops
self.assertTrue('softmax' in fwd_ops_new)

exe = paddle.static.Executor()
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2 changes: 1 addition & 1 deletion test/deprecated/prim/process/test_copy_op_deprecated.py
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Expand Up @@ -53,7 +53,7 @@ def cal_composite(self, inputs):
primapi.to_prim(blocks)

fwd_ops_new = [op.type for op in blocks[0].ops]
# Ensure that dropout is not splitted into small ops
# Ensure that dropout is not split into small ops
self.assertTrue('dropout' in fwd_ops_new)

exe = paddle.static.Executor()
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4 changes: 2 additions & 2 deletions test/prim/pir_prim/test_pir_prim_flags.py
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Expand Up @@ -43,7 +43,7 @@ def not_in_blacklist(self, op_name):
z = decomp.decompose(main_program, [z])

fwd_ops_new = [op.name() for op in main_program.global_block().ops]
# Ensure that tanh is splitted into small ops
# Ensure that tanh is split into small ops
self.assertTrue(op_name not in fwd_ops_new)

exe = paddle.static.Executor()
Expand Down Expand Up @@ -72,7 +72,7 @@ def in_blacklist(self, op_name):
z = decomp.decompose(main_program, [z])

fwd_ops_new = [op.name() for op in main_program.global_block().ops]
# Ensure that tanh is splitted into small ops
# Ensure that tanh is split into small ops
self.assertTrue(op_name in fwd_ops_new)

exe = paddle.static.Executor()
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