Autogenerate TTNN Tests for Explorer CI to consume

.github/workflows/build-and-test.yml

@@ -158,6 +158,12 @@ jobs:
         cmake --build ${{ steps.strings.outputs.build-output-dir }} -- check-ttmlir
         cp build/test/report.xml ${{ steps.strings.outputs.test_report_path }}
 
+    - name: Upload tests
+      uses: actions/upload-artifact@v4
+      with:
+        name: ${{ matrix.build.runs-on }}-${{ matrix.build.name }}-tests
+        path: ${{ steps.strings.outputs.build-output-dir }}/test
+
     - name: Upload Test Report
       uses: actions/upload-artifact@v4
       with:
@@ -640,9 +646,15 @@ jobs:
         source env/activate
         cmake --build ${{ steps.strings.outputs.build-output-dir }} -- explorer
 
+    - name: Download Tests
+      uses: actions/download-artifact@v4
+      with:
+        name: ${{ matrix.build.runs-on }}-${{ matrix.build.name }}-test
+
     - name: Run tt-explorer tests
       shell: bash
       run: |
         source env/activate
+        export TT_EXPLORER_GENERATED_TEST_DIR=${{ steps.strings.outputs.build-output-dir }}/test/ttmlir/Silicon/TTNN
         pytest tools/explorer/test/run_tests.py
         # collect results

CMakeLists.txt

@@ -9,6 +9,7 @@ option(TT_RUNTIME_ENABLE_PERF_TRACE "Enable performance mode" OFF)
 option(TTMLIR_ENABLE_RUNTIME "Enable runtime" OFF)
 option(TTMLIR_ENABLE_STABLEHLO "Enable StableHLO support" OFF)
 option(TTMLIR_ENABLE_OP_MODEL "Enable OpModel support" OFF)
+option(TT_EXPLORER_EDITABLE "Enable editable install mode for explorer" OFF)
 
 if (TTMLIR_ENABLE_STABLEHLO)
   add_compile_definitions(TTMLIR_ENABLE_STABLEHLO)

docs/src/tt-explorer.md

@@ -5,12 +5,11 @@ Welcome to the tt-explorer wiki! The Wiki will serve as a source for documentati
 ## Quick Start
 TT-Explorer is made to be as painless as possible, as such the installation on top of the pre-existing [`tt-mlir`](https://github.com/tenstorrent/tt-mlir) project is as minimal as possible.
 
-1. Build `tt-mlir`
+1. Build `tt-mlir`, add the `-DTT_EXPLORER_EDITABLE=ON` flag to the cmake build to install the `tt-explorer` package in editable mode.
 2. Run `source env/activate` to be in `tt-mlir` virtualenv for the following steps
-3. Install [`tt-adapter`](https://github.com/vprajapati-tt/tt-adapter) using `pip install -e .` in tt-adapter root directory.
-4. Install `tt-explorer` using `pip install -e .` in tt-explorer root directory
-5. Run `tt-explorer` in terminal to start tt-explorer instance. (Refer to CLI section in API for specifics)
-6. Ensure server has started in `tt-explorer` shell instance (check for message below)
+3. Install the explorer tool by building the `explorer` target using `cmake --build build -- explorer`
+4. Run `tt-explorer` in terminal to start tt-explorer instance. (Refer to CLI section in API for specifics)
+5. Ensure server has started in `tt-explorer` shell instance (check for message below)
 ```sh
 Starting Model Explorer server at:
 http://localhost:8080

tools/explorer/test/models/forward_and_backward.mlir → test/ttmlir/Explorer/load/forward_and_backward.mlir

@@ -1,3 +1,6 @@
+// RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s
+// Need to ensure that model is valid MLIR module
+
 module @SimpleModel attributes {} {
   func.func @forward(%arg0: tensor<1x784xf32> {ttir.name = "input_1"}, %arg1: tensor<10x784xf32> {ttir.name = "linear.weight"}, %arg2: tensor<10xf32> {ttir.name = "linear.bias"}) -> (tensor<1x10xf32> {ttir.name = "SimpleModel_472.output_softmax_1495"}) {
     %0 = tensor.empty() : tensor<784x10xf32>

tools/explorer/test/models/linear_autoencoder.mlir → test/ttmlir/Explorer/load/linear_autoencoder.mlir

@@ -1,3 +1,5 @@
+// RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s
+
 module @LinearAE attributes {} {
   func.func @forward(%arg0: tensor<1x784xf32> {ttir.name = "input_1"}, %arg1: tensor<784x128xf32> {ttir.name = "encoder_lin1.weight"}, %arg2: tensor<128xf32> {ttir.name = "encoder_lin1.bias"}, %arg3: tensor<128x64xf32> {ttir.name = "encoder_lin2.weight"}, %arg4: tensor<64xf32> {ttir.name = "encoder_lin2.bias"}, %arg5: tensor<64x12xf32> {ttir.name = "encoder_lin3.weight"}, %arg6: tensor<12xf32> {ttir.name = "encoder_lin3.bias"}, %arg7: tensor<12x3xf32> {ttir.name = "encoder_lin4.weight"}, %arg8: tensor<3xf32> {ttir.name = "encoder_lin4.bias"}, %arg9: tensor<3x12xf32> {ttir.name = "decoder_lin1.weight"}, %arg10: tensor<12xf32> {ttir.name = "decoder_lin1.bias"}, %arg11: tensor<12x64xf32> {ttir.name = "decoder_lin2.weight"}, %arg12: tensor<64xf32> {ttir.name = "decoder_lin2.bias"}, %arg13: tensor<64x128xf32> {ttir.name = "decoder_lin3.weight"}, %arg14: tensor<128xf32> {ttir.name = "decoder_lin3.bias"}, %arg15: tensor<128x784xf32> {ttir.name = "decoder_lin4.weight"}, %arg16: tensor<784xf32> {ttir.name = "decoder_lin4.bias"}) -> (tensor<1x784xf32> {ttir.name = "LinearAE.output_add_29"}) {
     %0 = tensor.empty() : tensor<1x128xf32>

tools/explorer/test/models/open_llama_3b_single_layer.mlir → test/ttmlir/Explorer/load/open_llama_3b_single_layer.mlir

@@ -1,3 +1,5 @@
+// RUN: ttmlir-opt --ttir-to-ttnn-backend-pipeline %s
+
 #any_device = #tt.operand_constraint<dram|l1|scalar|tile|none|interleaved|single_bank|height_sharded|width_sharded|block_sharded|any_layout|any_device|any_device_tile|l1_block_sharded>
 #loc = loc("LlamaForCausalLM":0:0)
 #system_desc = #tt.system_desc<[{role = host, target_triple = "x86_64-pc-linux-gnu"}], [{arch = <wormhole_b0>, grid = 8x8, l1_size = 1499136, num_dram_channels = 12, dram_channel_size = 1073741824, noc_l1_address_align_bytes = 16, pcie_address_align_bytes = 32, noc_dram_address_align_bytes = 32, l1_unreserved_base = 1024, erisc_l1_unreserved_base = 1024, dram_unreserved_base = 1024, dram_unreserved_end = 1073741824, physical_cores = {worker = [ 0x0,  0x1,  0x2,  0x3,  0x4,  0x5,  0x6,  0x7,  1x0,  1x1,  1x2,  1x3,  1x4,  1x5,  1x6,  1x7,  2x0,  2x1,  2x2,  2x3,  2x4,  2x5,  2x6,  2x7,  3x0,  3x1,  3x2,  3x3,  3x4,  3x5,  3x6,  3x7,  4x0,  4x1,  4x2,  4x3,  4x4,  4x5,  4x6,  4x7,  5x0,  5x1,  5x2,  5x3,  5x4,  5x5,  5x6,  5x7,  6x0,  6x1,  6x2,  6x3,  6x4,  6x5,  6x6,  6x7,  7x0,  7x1,  7x2,  7x3,  7x4,  7x5,  7x6,  7x7] dram = [ 8x0,  9x0,  10x0,  8x1,  9x1,  10x1,  8x2,  9x2,  10x2,  8x3,  9x3,  10x3]}, supported_data_types = [<f32>, <f16>, <bf16>, <bfp_f8>, <bfp_bf8>, <bfp_f4>, <bfp_bf4>, <bfp_f2>, <bfp_bf2>, <u32>, <u16>, <u8>], supported_tile_sizes = [ 4x16,  16x16,  32x16,  4x32,  16x32,  32x32], num_cbs = 32}], [0], [3 : i32], [ 0x0x0x0]>

tools/explorer/CMakeLists.txt

@@ -15,9 +15,15 @@ ExternalProject_Add(
   INSTALL_COMMAND ""
 )
 
+set(PIP_EDITABLE_FLAG "")
+
+if (TT_EXPLORER_EDITABLE)
+  set(PIP_EDITABLE_FLAG "-e")
+endif()
+
 add_custom_target(explorer
   COMMENT "Building tt-explorer... ${TTMLIR_BIN_DIR}"
-  COMMAND pip install $<$<CONFIG:Debug>:-e> ${CMAKE_CURRENT_SOURCE_DIR}/tt_adapter
+  COMMAND pip install ${PIP_EDITABLE_FLAG} ${CMAKE_CURRENT_SOURCE_DIR}/tt_adapter
   COMMAND pip install ${CMAKE_CURRENT_SOURCE_DIR}/model-explorer/src/model-explorer/src/server/package
 
   DEPENDS TTMLIRPythonModules model-explorer ttrt

tools/explorer/run.py

@@ -9,4 +9,4 @@
 # TODO(odjuricic): Hack to make our extension default for .mlir files.
 # This can be handled better when we switch to our model-explorer fork.
 model_explorer.extension_manager.ExtensionManager.BUILTIN_ADAPTER_MODULES = []
-model_explorer.visualize(extensions=["tt_adapter"])
+model_explorer.visualize_from_config(extensions=["tt_adapter"], no_open_in_browser=True)

tools/explorer/test/run_tests.py

@@ -8,23 +8,29 @@
 import multiprocessing
 import pytest
 import glob
+import os
 
 HOST = "localhost"
 PORT = 8002
 COMMAND_URL = "http://" + HOST + ":" + str(PORT) + "/apipost/v1/send_command"
 TEST_LOAD_MODEL_PATHS = [
     "test/ttmlir/Dialect/TTNN/optimizer/mnist_sharding.mlir",
-    "tools/explorer/test/models/*.mlir",
+    "test/ttmlir/Explorer/*.mlir",
 ]
 TEST_EXECUTE_MODEL_PATHS = [
     "test/ttmlir/Silicon/TTNN/optimizer/mnist_sharding_tiled.mlir",
 ]
 
+if "TT_EXPLORER_GENERATED_TEST_DIR" in os.environ:
+    TEST_LOAD_MODEL_PATHS.append(
+        os.environ["TT_EXPLORER_GENERATED_TEST_DIR"] + "/**/*.mlir"
+    )
+
 
 def get_test_files(paths):
     files = []
     for path in paths:
-        files.extend(glob.glob(path))
+        files.extend(glob.glob(path, recursive=True))
     return files
 
 
@@ -47,8 +53,13 @@ def execute_command(model_path, settings):
 @pytest.fixture(scope="function", autouse=True)
 def start_server(request):
     server_thread = multiprocessing.Process(
-        target=model_explorer.visualize,
-        kwargs={"extensions": ["tt_adapter"], "host": HOST, "port": PORT},
+        target=model_explorer.visualize_from_config,
+        kwargs={
+            "extensions": ["tt_adapter"],
+            "host": HOST,
+            "port": PORT,
+            "no_open_in_browser": True,
+        },
     )
     server_thread.start()