[AMP] Audit mixed precision operation schedules for correctness

[AndrewZhaoLuo]

Some operations like conv2d and matmul support heterogenous output datatypes.

E.g. the operation could be done with float16 operands but accumulate the result in float32.

However, some schedules for these ops don't actually support mixed precision types. For example python/tvm/topi/cuda/conv2d_winograd.py has a type error if the output dtype is not the same as the input dtypes.

This issue is to audit operations which support output datatypes (e.g. have the out_dtype attribute) and make sure corresponding schedules support the feature. For every schedule this will involve adding a unittest.

List of ops to examine

• "nn.conv1d",
• "nn.conv2d",
• "nn.conv3d",
• "nn.conv1d_transpose",
• "nn.conv2d_transpose",
• "nn.conv3d_transpose",
• "nn.dense",
• "nn.batch_matmul"

[AndrewZhaoLuo]

#8517 might fix this if it is not too controversial.

[AndrewZhaoLuo]

Closing as #8517 should have fixed this.