docs: showcase remove mnist_gan and add conversation.py (#4757)

fixed both examples, and i think it's better to show conversation

docs/showcase.md

@@ -33,12 +33,6 @@ SMALL=1 python3 examples/whisper.py
 
 ## Generative
 
-### Generative Adversarial Networks
-
-Take a look at [mnist_gan.py](https://github.com/tinygrad/tinygrad/tree/master/examples/mnist_gan.py).
-
-![mnist gan by tinygrad](https://github.com/tinygrad/tinygrad/blob/master/docs/showcase/mnist_by_tinygrad.jpg?raw=true)
-
 ### Stable Diffusion
 
 ```sh
@@ -57,3 +51,12 @@ Then you can have a chat with Stacy:
 ```sh
 python3 examples/llama.py
 ```
+
+### Conversation
+
+Make sure you have espeak installed and `PHONEMIZER_ESPEAK_LIBRARY` set.
+
+Then you can talk to Stacy:
+```sh
+python3 examples/conversation.py
+```

examples/mnist_gan.py

@@ -88,6 +88,7 @@ if __name__ == "__main__":
   optim_g = optim.Adam(get_parameters(generator),lr=0.0002, b1=0.5)  # 0.0002 for equilibrium!
   optim_d = optim.Adam(get_parameters(discriminator),lr=0.0002, b1=0.5)
   # training loop
+  Tensor.training = True
   for epoch in (t := trange(epochs)):
     loss_g, loss_d = 0.0, 0.0
     for _ in range(n_steps):

examples/vits.py

@@ -487,7 +487,7 @@ def split(tensor, split_sizes, dim=0):  # if split_sizes is an integer, convert
     slice_range = [(start, start + size) if j == dim else None for j in range(len(tensor.shape))]
     slices.append(slice_range)
     start += size
-  return [tensor.slice(s) for s in slices]
+  return [tensor._slice(s) for s in slices]
 def gather(x, indices, axis):
   indices = (indices < 0).where(indices + x.shape[axis], indices).transpose(0, axis)
   permute_args = list(range(x.ndim))

extra/threefry.py

@@ -4,7 +4,7 @@ if "THREEFRY" not in os.environ: os.environ["THREEFRY"] = "1"
 
 from tinygrad import Tensor, GlobalCounters
 
-for N in [10, 100, 1_000, 10_000, 100_000, 1_000_000, 10_000_000, 100_000_000, 1_000_000_000]:
+for N in [10_000_000, 100_000_000, 1_000_000_000]:
   GlobalCounters.reset()
   Tensor.rand(N).realize()
   print(f"N {N:>20_}, global_ops {GlobalCounters.global_ops:>20_}, global_mem {GlobalCounters.global_mem:>20_}")