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@ -1858,14 +1858,14 @@ def density_prior_box(input,
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.. code-block:: python
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#declarative mode
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#declarative mode
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import paddle.fluid as fluid
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import numpy as np
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import paddle.fluid as fluid
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import numpy as np
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input = fluid.data(name="input", shape=[None,3,6,9])
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image = fluid.data(name="image", shape=[None,3,9,12])
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box, var = fluid.layers.density_prior_box(
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input = fluid.data(name="input", shape=[None,3,6,9])
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image = fluid.data(name="image", shape=[None,3,9,12])
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box, var = fluid.layers.density_prior_box(
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input=input,
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image=image,
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densities=[4, 2, 1],
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@ -1874,45 +1874,45 @@ def density_prior_box(input,
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clip=True,
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flatten_to_2d=True)
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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exe.run(fluid.default_startup_program())
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# prepare a batch of data
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input_data = np.random.rand(1,3,6,9).astype("float32")
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image_data = np.random.rand(1,3,9,12).astype("float32")
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place = fluid.CPUPlace()
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exe = fluid.Executor(place)
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exe.run(fluid.default_startup_program())
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box_out, var_out = exe.run(
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fluid.default_main_program(),
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# prepare a batch of data
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input_data = np.random.rand(1,3,6,9).astype("float32")
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image_data = np.random.rand(1,3,9,12).astype("float32")
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box_out, var_out = exe.run(
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fluid.default_main_program(),
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feed={"input":input_data,
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"image":image_data},
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"image":image_data},
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fetch_list=[box,var],
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return_numpy=True)
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print(mask_out.shape)
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# (1134, 4)
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print(z_out.shape)
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# (1134, 4)
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# print(box_out.shape)
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# (1134, 4)
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# print(var_out.shape)
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# (1134, 4)
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#imperative mode
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import paddle.fluid.dygraph as dg
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with dg.guard(place) as g:
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input = dg.to_variable(input_data)
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image = dg.to_variable(image_data)
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box, var = fluid.layers.density_prior_box(
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input=input,
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image=image,
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densities=[4, 2, 1],
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fixed_sizes=[32.0, 64.0, 128.0],
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fixed_ratios=[1.],
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clip=True)
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print(box.shape)
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# [6L, 9L, 21L, 4L]
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print(var.shape)
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# [6L, 9L, 21L, 4L]
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#imperative mode
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import paddle.fluid.dygraph as dg
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with dg.guard(place) as g:
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input = dg.to_variable(input_data)
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image = dg.to_variable(image_data)
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box, var = fluid.layers.density_prior_box(
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input=input,
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image=image,
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densities=[4, 2, 1],
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fixed_sizes=[32.0, 64.0, 128.0],
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fixed_ratios=[1.],
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clip=True)
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# print(box.shape)
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# [6L, 9L, 21L, 4L]
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# print(var.shape)
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# [6L, 9L, 21L, 4L]
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"""
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helper = LayerHelper("density_prior_box", **locals())
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