Comments (2)
Start of the notebook should be fine, but we shouldn't change the cells where it is set explicitly.
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As torch.manual_seed()
is creating a generator, it should be sufficient to set it once at the start of each notebook.
Or does a seed per cell (given that any numbers are generated) have any other advantages?
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Related Issues (20)
- update dependencies=2.0.1 requirement HOT 4
- Mac OSX Tests for `torch==1.9.1` fail when installing dependencies HOT 3
- Weights not quantized after using qnn.QuantConv2d layers for QAT HOT 1
- Missing minifloat testing
- List of all the avalable quantization strategies HOT 3
- Using external activation functions HOT 4
- Custom bit-width and QuantTensor Operation HOT 4
- Docstrings with backslashes are not set as raw strings HOT 1
- Assign scale value for QuantIdentity() HOT 2
- BrevitasQuantProxyHandler args passing may be sometimes wrong HOT 9
- Tests: Update QONNX export tests to include property, accuracy validation
- Feature Request: More padding mode. HOT 4
- Replace QuantTensor -> <Datatype>QuantTensor in notebooks
- Functionalise Hadamard classifier Module
- Modify layers in a pretrained Brevitas Model HOT 1
- Add tests for TruncAvgPool
- `ConvXd` -> `QuantConvXd` fails when `padding='same'` HOT 1
- Unsigned quantization of activation function HOT 5
- Move DelayWrapper logic to Proxy HOT 2
- Bug in float quant proxy properties is_fnuz and is_ocp
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