From fe617f95fb6805faa8c4960f16e8c3cd492ba3d0 Mon Sep 17 00:00:00 2001
From: 201716010711 <87008376+201716010711@users.noreply.github.com>
Date: Mon, 28 Nov 2022 13:27:55 +0800
Subject: [PATCH] delete gaussian_random_batch_size_like api (#48394)

---
 python/paddle/fluid/layers/nn.py              | 81 -------------------
 .../fluid/tests/unittests/test_layers.py      | 14 ----
 2 files changed, 95 deletions(-)

diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 3e40a80216a..ac080de1ff9 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -117,7 +117,6 @@ __all__ = [
     'elementwise_mul',
     'gaussian_random',
     'sampling_id',
-    'gaussian_random_batch_size_like',
     'sum',
     'slice',
     'shape',
@@ -7029,86 +7028,6 @@ def sampling_id(x, min=0.0, max=1.0, seed=0, dtype='float32'):
     return out
 
 
-@deprecated(since='1.8.0', update_to="paddle.normal")
-@templatedoc()
-def gaussian_random_batch_size_like(
-    input,
-    shape,
-    input_dim_idx=0,
-    output_dim_idx=0,
-    mean=0.0,
-    std=1.0,
-    seed=0,
-    dtype='float32',
-):
-    """
-    ${comment}
-
-    Args:
-        input (Variable): ${input_comment}
-        shape (tuple|list): ${shape_comment}
-        input_dim_idx (int): ${input_dim_idx_comment}
-        output_dim_idx (int): ${output_dim_idx_comment}
-        mean (float): ${mean_comment}
-        std (float): ${std_comment}
-        seed (int): ${seed_comment}
-        dtype(np.dtype|core.VarDesc.VarType|str): The type of output data, float32 or float_64.
-
-    Returns:
-        out (Variable): ${out_comment}
-
-    Examples:
-        .. code-block:: python
-
-            import paddle
-            import paddle.fluid as fluid
-            paddle.enable_static()
-
-            input = fluid.data(name="input", shape=[13, 11], dtype='float32')
-
-            out = fluid.layers.gaussian_random_batch_size_like(
-                input, shape=[-1, 11], mean=1.0, std=2.0)
-    """
-
-    helper = LayerHelper('gaussian_random_batch_size_like', **locals())
-    check_type(
-        input,
-        'input',
-        (Variable),
-        'fluid.layers.gaussian_random_batch_size_like',
-    )
-    check_type(
-        shape,
-        'shape',
-        (list, tuple),
-        'fluid.layers.gaussian_random_batch_size_like',
-    )
-    check_dtype(
-        dtype,
-        'dtype',
-        ['float16', 'float32', 'int'],
-        'fluid.layers.gaussian_random_batch_size_like',
-    )
-    out = helper.create_variable_for_type_inference(dtype)
-    c_dtype = convert_np_dtype_to_dtype_(dtype)
-    helper.append_op(
-        type='gaussian_random_batch_size_like',
-        inputs={'Input': input},
-        outputs={'Out': out},
-        attrs={
-            'shape': shape,
-            'input_dim_idx': input_dim_idx,
-            'output_dim_idx': output_dim_idx,
-            'mean': mean,
-            'std': std,
-            'seed': seed,
-            'dtype': c_dtype,
-        },
-    )
-
-    return out
-
-
 @templatedoc()
 def sum(x):
     """
diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py
index aff461f8786..fb0bb9827f6 100644
--- a/python/paddle/fluid/tests/unittests/test_layers.py
+++ b/python/paddle/fluid/tests/unittests/test_layers.py
@@ -2921,7 +2921,6 @@ class TestBook(LayerTest):
         self.not_compare_static_dygraph_set = set(
             {
                 "make_gaussian_random",
-                "make_gaussian_random_batch_size_like",
                 "make_kldiv_loss",
                 "make_prelu",
                 "make_sampling_id",
@@ -3580,19 +3579,6 @@ class TestBook(LayerTest):
             out = layers.sampling_id(x)
             return out
 
-    def make_gaussian_random_batch_size_like(self):
-        with program_guard(
-            fluid.default_main_program(), fluid.default_startup_program()
-        ):
-            input = self._get_data(
-                name="input", shape=[13, 11], dtype='float32'
-            )
-
-            out = layers.gaussian_random_batch_size_like(
-                input, shape=[-1, 11], mean=1.0, std=2.0
-            )
-            return out
-
     def make_sum(self):
         with program_guard(
             fluid.default_main_program(), fluid.default_startup_program()
-- 
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