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Activity for daniel_s
| Type | On... | Excerpt | Status | Date |
|---|---|---|---|---|
| Edit | Post #289625 |
Post edited: |
— | about 1 year ago |
| Comment | Post #289613 |
Yes. Tensorflow is intended to be executed on GPUs or TPUs, special hardware for doing calculations in parallel. The marker for executing it in parallel is the @tf.function decorator. Inside functions which have this decorator, (when executed on a GPU or TPU) you can't use all standard python modules... (more) |
— | about 1 year ago |
| Comment | Post #289625 |
After more testing of lin_to_db I realized it doesn't work in all places with the pure tensorflow version, because it always returns a tf.Tensor, no matter if the input is a tf.Tensor or a float. But some subsequent code (in my case, json.dumps) can't handle tf.Tensor:
TypeError: Object of type Eage... (more) |
— | about 1 year ago |
| Comment | Post #289625 |
Cool, you're right, at least for lin_to_db I can indeed use just the tensorflow version.
The other one is a bit more tricky, because I have variables which contain values that get written before graph execution and they get read during graph execution and afterwards. I don't want to duplicate them... (more) |
— | about 1 year ago |
| Edit | Post #289625 |
Post edited: |
— | about 1 year ago |
| Edit | Post #289625 | Initial revision | — | about 1 year ago |
| Question | — |
Best practices to write functions for both execution modes in Tensorflow, eager and graph mode I regularly run into the problem that I have a Python function that I want to use in both, eager and graph execution mode. I therefore have to adjust the code so that it can handle both situations. Here are two examples: ```python import tensorflow as tf ``` ```python def lintodb(x: float | tf... (more) |
— | about 1 year ago |
| Edit | Post #289613 | Initial revision | — | about 1 year ago |
| Question | — |
Can't use tf.timestamp() from within @tf.function with XLA / jit_compile=True I would like to use `tf.timestamp()` when it is available (eager mode and graph mode without XLA), and use `0.` (or a better fallback if there is one) when it is not available (with XLA; `@tf.function(jitcompile=True)`). I tried this: def tftimestamporzero(): try: retu... (more) |
— | about 1 year ago |
| Edit | Post #289588 |
Post edited: |
— | about 1 year ago |
| Edit | Post #289588 |
Post edited: |
— | about 1 year ago |
| Edit | Post #289588 |
Post edited: |
— | about 1 year ago |
| Edit | Post #289588 | Initial revision | — | about 1 year ago |
| Question | — |
Is it okay to use python operators for tensorflow tensors? TL;DR - Is `(a and b)` equivalent to `tf.logicaland(a, b)` in terms of optimization and performance? (`a` and `b` are tensorflow tensors) Details - I use Python with Tensorflow. My priorities are 1. Make the code run fast 2. Make it readable. I have working and fast code that, for my ... (more) |
— | about 1 year ago |