mirror of
https://github.com/saymrwulf/pytorch.git
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032d6b0643
Test Plan: revert-hammer
Differential Revision:
D28112689 (1416e57465)
Original commit changeset: f825cd4bce40
fbshipit-source-id: 421fc590797ac5fab6a55ac6f213361fbba7cd5b
236 lines
10 KiB
Text
236 lines
10 KiB
Text
# shape: torch.Size([10, 10])
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# nnz: 10
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# crow_indices shape: torch.Size([11])
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# col_indices shape: torch.Size([10])
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# values_shape: torch.Size([10])
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########## torch.float32/torch.int32 ##########
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# sparse tensor
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tensor(crow_indices=tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),
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col_indices=tensor([5, 1, 6, 5, 6, 4, 2, 5, 5, 9]),
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values=tensor([ 0.5674, 0.1261, 0.5497, 0.6416, -0.4414, 0.3634,
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-0.4327, 0.3135, -0.5225, 0.4626]), size=(10, 10),
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nnz=10)
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# _crow_indices
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tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
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# _col_indices
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tensor([5, 1, 6, 5, 6, 4, 2, 5, 5, 9])
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# _values
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tensor([ 0.5674, 0.1261, 0.5497, 0.6416, -0.4414, 0.3634, -0.4327, 0.3135,
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-0.5225, 0.4626])
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########## torch.float64/torch.int32 ##########
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# sparse tensor
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tensor(crow_indices=tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),
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col_indices=tensor([8, 2, 0, 4, 9, 2, 1, 9, 2, 2]),
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values=tensor([ 0.3324, -0.3314, 0.5786, -0.3567, 0.0494, 0.3377,
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0.6872, -0.1470, 0.9123, -0.8460]), size=(10, 10),
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nnz=10)
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# _crow_indices
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tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
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# _col_indices
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tensor([8, 2, 0, 4, 9, 2, 1, 9, 2, 2])
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# _values
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tensor([ 0.3324, -0.3314, 0.5786, -0.3567, 0.0494, 0.3377, 0.6872, -0.1470,
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0.9123, -0.8460])
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########## torch.float32/torch.int64 ##########
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# sparse tensor
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tensor(crow_indices=tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),
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col_indices=tensor([1, 5, 2, 1, 7, 4, 3, 0, 7, 6]),
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values=tensor([ 0.5056, 0.7977, 0.3677, 0.5317, 0.8298, -0.2015,
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-0.7799, -0.4918, -0.1335, -0.1099]), size=(10, 10),
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nnz=10)
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# _crow_indices
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tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
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# _col_indices
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tensor([1, 5, 2, 1, 7, 4, 3, 0, 7, 6])
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# _values
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tensor([ 0.5056, 0.7977, 0.3677, 0.5317, 0.8298, -0.2015, -0.7799, -0.4918,
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-0.1335, -0.1099])
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########## torch.float64/torch.int64 ##########
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# sparse tensor
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tensor(crow_indices=tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]),
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col_indices=tensor([6, 3, 4, 8, 5, 1, 5, 6, 4, 2]),
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values=tensor([-0.2544, -0.2462, -0.9784, 0.8910, 0.5322, -0.4732,
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-0.6239, 0.0348, 0.5698, -0.7176]), size=(10, 10),
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nnz=10)
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# _crow_indices
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tensor([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
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# _col_indices
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tensor([6, 3, 4, 8, 5, 1, 5, 6, 4, 2])
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# _values
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tensor([-0.2544, -0.2462, -0.9784, 0.8910, 0.5322, -0.4732, -0.6239, 0.0348,
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0.5698, -0.7176])
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# shape: torch.Size([100, 10])
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# nnz: 10
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# crow_indices shape: torch.Size([101])
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# col_indices shape: torch.Size([10])
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# values_shape: torch.Size([10])
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########## torch.float32/torch.int32 ##########
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# sparse tensor
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tensor(crow_indices=tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),
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col_indices=tensor([7, 4, 5, 2, 8, 8, 8, 8, 4, 4]),
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values=tensor([ 0.0548, 0.2650, -0.8181, -0.5354, 0.4537, -0.7625,
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-0.2098, 0.4398, 0.5190, 0.0622]), size=(100, 10),
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nnz=10)
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# _crow_indices
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tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0])
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# _col_indices
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tensor([7, 4, 5, 2, 8, 8, 8, 8, 4, 4])
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# _values
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tensor([ 0.0548, 0.2650, -0.8181, -0.5354, 0.4537, -0.7625, -0.2098, 0.4398,
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0.5190, 0.0622])
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########## torch.float64/torch.int32 ##########
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# sparse tensor
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tensor(crow_indices=tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),
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col_indices=tensor([8, 9, 2, 9, 3, 4, 9, 2, 6, 2]),
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values=tensor([ 0.0069, -0.3837, -0.2516, -0.1406, 0.9457, 0.9479,
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-0.0935, -0.3003, 0.4856, -0.0798]), size=(100, 10),
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nnz=10)
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# _crow_indices
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tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0])
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# _col_indices
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tensor([8, 9, 2, 9, 3, 4, 9, 2, 6, 2])
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# _values
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tensor([ 0.0069, -0.3837, -0.2516, -0.1406, 0.9457, 0.9479, -0.0935, -0.3003,
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0.4856, -0.0798])
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########## torch.float32/torch.int64 ##########
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# sparse tensor
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tensor(crow_indices=tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),
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col_indices=tensor([1, 2, 3, 2, 1, 2, 7, 4, 7, 6]),
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values=tensor([ 0.5833, 0.0894, 0.2440, -0.6665, -0.2136, 0.6597,
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0.4587, -0.2891, 0.1230, 0.7656]), size=(100, 10),
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nnz=10)
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# _crow_indices
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tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0])
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# _col_indices
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tensor([1, 2, 3, 2, 1, 2, 7, 4, 7, 6])
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# _values
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tensor([ 0.5833, 0.0894, 0.2440, -0.6665, -0.2136, 0.6597, 0.4587, -0.2891,
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0.1230, 0.7656])
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########## torch.float64/torch.int64 ##########
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# sparse tensor
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tensor(crow_indices=tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]),
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col_indices=tensor([6, 1, 5, 9, 0, 8, 6, 1, 0, 9]),
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values=tensor([-0.2178, 0.7886, 0.3778, 0.6779, -0.6440, 0.2883,
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0.1788, 0.1743, 0.9286, 0.5536]), size=(100, 10),
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nnz=10)
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# _crow_indices
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tensor([0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
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0, 0, 0, 0, 0])
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# _col_indices
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tensor([6, 1, 5, 9, 0, 8, 6, 1, 0, 9])
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# _values
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tensor([-0.2178, 0.7886, 0.3778, 0.6779, -0.6440, 0.2883, 0.1788, 0.1743,
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0.9286, 0.5536])
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# shape: torch.Size([1000, 10])
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# nnz: 10
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# crow_indices shape: torch.Size([1001])
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# col_indices shape: torch.Size([10])
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# values_shape: torch.Size([10])
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########## torch.float32/torch.int32 ##########
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# sparse tensor
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tensor(crow_indices=tensor([0, 0, 0, ..., 0, 0, 0]),
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col_indices=tensor([5, 4, 4, 0, 5, 6, 8, 0, 2, 8]),
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values=tensor([-0.2851, -0.7618, 0.9845, 0.7515, 0.4756, 0.9898,
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-0.5324, -0.5695, -0.5853, -0.0484]), size=(1000, 10),
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nnz=10)
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# _crow_indices
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tensor([0, 0, 0, ..., 0, 0, 0])
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# _col_indices
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tensor([5, 4, 4, 0, 5, 6, 8, 0, 2, 8])
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# _values
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tensor([-0.2851, -0.7618, 0.9845, 0.7515, 0.4756, 0.9898, -0.5324, -0.5695,
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-0.5853, -0.0484])
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########## torch.float64/torch.int32 ##########
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# sparse tensor
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tensor(crow_indices=tensor([0, 0, 0, ..., 0, 0, 0]),
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col_indices=tensor([3, 6, 2, 3, 7, 8, 6, 7, 7, 2]),
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values=tensor([ 0.3105, -0.6785, -0.1184, -0.2653, 0.4315, 0.6985,
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0.2432, -0.0908, -0.2561, 0.7840]), size=(1000, 10),
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nnz=10)
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# _crow_indices
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tensor([0, 0, 0, ..., 0, 0, 0])
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# _col_indices
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tensor([3, 6, 2, 3, 7, 8, 6, 7, 7, 2])
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# _values
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tensor([ 0.3105, -0.6785, -0.1184, -0.2653, 0.4315, 0.6985, 0.2432, -0.0908,
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-0.2561, 0.7840])
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########## torch.float32/torch.int64 ##########
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# sparse tensor
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tensor(crow_indices=tensor([0, 0, 0, ..., 0, 0, 0]),
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col_indices=tensor([2, 3, 1, 1, 0, 2, 5, 9, 3, 0]),
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values=tensor([ 0.3443, -0.2613, 0.1793, 0.5857, -0.9265, -0.9102,
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-0.5984, 0.1220, -0.1854, 0.2155]), size=(1000, 10),
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nnz=10)
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# _crow_indices
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tensor([0, 0, 0, ..., 0, 0, 0])
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# _col_indices
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tensor([2, 3, 1, 1, 0, 2, 5, 9, 3, 0])
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# _values
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tensor([ 0.3443, -0.2613, 0.1793, 0.5857, -0.9265, -0.9102, -0.5984, 0.1220,
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-0.1854, 0.2155])
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########## torch.float64/torch.int64 ##########
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# sparse tensor
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tensor(crow_indices=tensor([0, 0, 0, ..., 0, 0, 0]),
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col_indices=tensor([3, 7, 7, 9, 7, 7, 6, 6, 9, 2]),
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values=tensor([ 0.3393, -0.9329, -0.8195, 0.5085, 0.4854, -0.9112,
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0.7196, -0.1944, 0.7424, -0.5868]), size=(1000, 10),
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nnz=10)
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# _crow_indices
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tensor([0, 0, 0, ..., 0, 0, 0])
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# _col_indices
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tensor([3, 7, 7, 9, 7, 7, 6, 6, 9, 2])
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# _values
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tensor([ 0.3393, -0.9329, -0.8195, 0.5085, 0.4854, -0.9112, 0.7196, -0.1944,
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0.7424, -0.5868])
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