#0: adding new reshape sweeps and correcting existing ones (#15866)

### Problem description
Adding the new torch sweeps for reshape

### What's changed
Added torch sweeps to reshape
Added a parser for their new format
Updated reshape.reshape test to test for bfloat16 and float32 rather
than bfloat8 and bfloat16

### Checklist
- [x] Post commit CI passes
https://github.com/tenstorrent/tt-metal/actions/runs/12269839018
- [ ] Blackhole Post commit (if applicable)
- [ ] Model regression CI testing passes (if applicable)
- [ ] Device performance regression CI testing passes (if applicable)
- [ ] **(For models and ops writers)** Full [new
models](https://github.com/tenstorrent/tt-metal/actions/workflows/full-new-models-suite.yaml)
tests passes
- [ ] New/Existing tests provide coverage for changes

.github/workflows/ttnn-run-sweeps.yaml

@@ -356,6 +356,7 @@ on:
           - data_movement.squeeze.squeeze_pytorch2
           - data_movement.embedding.embedding_pytorch2
           - data_movement.view.view_pytorch2
+          - data_movement.view.view_tt_torch
   schedule:
     - cron: "0 21 * * *" # This cron schedule runs the workflow at 9:00pm UTC nightly
 

tests/sweep_framework/sweeps/data_movement/reshape/reshape.py

@@ -67,8 +67,8 @@ def gen_reshape_shape(input_shape, step=1):
         "input_shape": gen_shapes([1, 1, 1, 1], [6, 6, 256, 256], [1, 1, 1, 1], 16)
         + gen_shapes([1, 1, 1], [6, 256, 256], [1, 1, 1], 16)
         + gen_shapes([1, 1], [256, 256], [1, 1], 16),
-        "input_a_dtype": [ttnn.bfloat16, ttnn.bfloat8_b],
-        "input_a_layout": [ttnn.TILE_LAYOUT],  # ttnn.ROW_MAJOR_LAYOUT
+        "input_a_dtype": [ttnn.bfloat16, ttnn.float32],
+        "input_a_layout": [ttnn.TILE_LAYOUT, ttnn.ROW_MAJOR_LAYOUT],  # ttnn.ROW_MAJOR_LAYOUT
         "input_a_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
     },
 }