Comments (1)
We might be at the point where we can now fix this if we can treat distributed values as datasets.
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Related Issues (20)
- Can't find external classes HOT 7
- Make `com.ibm.wala.cast.python.ml.test` use Jython3 HOT 2
- Pytest entrypoints don't work when importing libraries HOT 2
- Using the same list of tensors to represent different lists in keras models
- Can't track modules with the same name in different directories
- No notion of PYTHONPATH in analysis HOT 6
- Track individual tensors in containers (datasets, tuples, etc) HOT 2
- Track tensors emanating from `tf.data.Dataset.enumerate()` HOT 2
- Track tensors emanating from `tf.data.Dataset.zip()` HOT 1
- Order of modules matters
- `tf.Tensor` used as a type is coming up as a tensor instance
- Importing a module on the PYTHONPATH doesn't work
- Importing a module for a package on a PYTHONPATH doesn't work
- Resolving relative imports does not consider the entire module path HOT 2
- No argument expansion for custom decorators with function parameters HOT 1
- Missing custom decorators with decorator parameters HOT 4
- Missing decorated functions whose decorators simply return the function HOT 4
- Log decorators being used
- Not tracking tensors returned by `tf.reshape()` for data sources other than MNIST HOT 5
- Decorated functions specifying a PYTHONPATH don't show up in the call graph HOT 1
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