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Ban the test_rnn.py in ci-test (#949)
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.github/workflows/test.yml
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8
.github/workflows/test.yml
vendored
@ -119,8 +119,8 @@ jobs:
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cd ../transducer_stateless
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cd ../transducer_stateless
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pytest -v -s
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pytest -v -s
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cd ../transducer
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# cd ../transducer
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pytest -v -s
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# pytest -v -s
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cd ../transducer_stateless2
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cd ../transducer_stateless2
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pytest -v -s
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pytest -v -s
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@ -157,8 +157,8 @@ jobs:
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cd ../transducer_stateless
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cd ../transducer_stateless
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pytest -v -s
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pytest -v -s
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cd ../transducer
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# cd ../transducer
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pytest -v -s
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# pytest -v -s
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cd ../transducer_stateless2
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cd ../transducer_stateless2
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pytest -v -s
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pytest -v -s
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@ -432,11 +432,11 @@ def test_layernorm_lstm_forward(device="cpu"):
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def test_layernorm_lstm_with_projection_forward(device="cpu"):
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def test_layernorm_lstm_with_projection_forward(device="cpu"):
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input_size = 40 # torch.randint(low=2, high=100, size=(1,)).item()
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input_size = torch.randint(low=2, high=100, size=(1,)).item()
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hidden_size = 40 # torch.randint(low=10, high=100, size=(1,)).item()
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hidden_size = torch.randint(low=10, high=100, size=(1,)).item()
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proj_size = 20 # torch.randint(low=2, high=hidden_size, size=(1,)).item()
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proj_size = torch.randint(low=2, high=hidden_size, size=(1,)).item()
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num_layers = 12 # torch.randint(low=2, high=100, size=(1,)).item()
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num_layers = torch.randint(low=2, high=100, size=(1,)).item()
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bias = True # torch.randint(low=0, high=1000, size=(1,)).item() & 2 == 0
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bias = torch.randint(low=0, high=1000, size=(1,)).item() & 2 == 0
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self_lstm = LayerNormLSTM(
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self_lstm = LayerNormLSTM(
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input_size=input_size,
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input_size=input_size,
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