# Reproducibility

Source: https://www.tensorplay.cn/docs/deterministic.html

If an operation depends on randomness or on non-deterministic kernels (for example some
parallel reductions, or GPU kernels), two runs may not produce bit-identical results. TensorPlay
provides a set of helpers to request deterministic algorithms and to detect when one is in use.

```
import tensorplay as tp

print(tp.are_deterministic_algorithms_enabled())   # False by default
tp.use_deterministic_algorithms(True)
print(tp.are_deterministic_algorithms_enabled())   # True
```

use_deterministic_algorithms is the main switch. When enabled, TensorPlay raises an error for
operations that cannot be run deterministically, so you can find them instead of silently
getting a different answer.

```
tp.use_deterministic_algorithms(True, warn_only=True)
```

Passing warn_only=True downgrades that error to a warning, which is useful for tracking down
culprits without stopping mid-run. tp.is_deterministic_algorithms_warn_only_enabled() reports
whether you are in that mode.

There is also a debug mode that tells you which operation is at fault:

```
tp.set_deterministic_debug_mode(True)   # report the offending op
tp.get_deterministic_debug_mode()       # read the mode back
```

| tensorplay.use_deterministic_algorithms |Sets whether TensorPlay operations must use "deterministic" algorithms. |
| --- | --- |
| tensorplay.are_deterministic_algorithms_enabled | Returns True if the global deterministic flag is turned on. |
| tensorplay.is_deterministic_algorithms_warn_only_enabled | Returns True if the global deterministic flag is set to warn only. |
| tensorplay.set_deterministic_debug_mode | Sets the debug mode for deterministic operations. |
| tensorplay.get_deterministic_debug_mode | Returns the current value of the debug mode for deterministic operations. |

## Seeding for random tensors

Deterministic algorithms are about how an op is computed. For the random values themselves,
control the seed with tensorplay.random (see the [random](/docs/random.html) page).

## Where to go next

- [Randomness](/docs/notes/randomness.html) — reproducibility across runs and processes.