| """ |
| The following instruction is based on web/README.md. |
| |
| Setup an RPC server: |
| $ python -m tvm.exec.rpc_proxy --example-rpc=1 |
| |
| Go to http://localhost:9190 in browser. |
| |
| Click "Connect To Proxy". |
| |
| Run this test script: |
| $ python tests/webgl/test_remote_save_load.py |
| """ |
| |
| import numpy as np |
| import tvm |
| from tvm import rpc |
| from tvm.contrib import util, emscripten |
| |
| proxy_host = "localhost" |
| proxy_port = 9090 |
| |
| def try_remote_save_load(): |
| if not tvm.module.enabled("rpc"): |
| return |
| if not tvm.module.enabled("opengl"): |
| return |
| if not tvm.module.enabled("llvm"): |
| return |
| |
| # Build the module. |
| n = tvm.var("n") |
| A = tvm.placeholder((n,), name='A') |
| B = tvm.placeholder((n,), name='B') |
| C = tvm.compute(A.shape, lambda i: A[i] + B[i], name="C") |
| s = tvm.create_schedule(C.op) |
| s[C].opengl() |
| target_host = "llvm -target=asmjs-unknown-emscripten -system-lib" |
| f = tvm.build(s, [A, B, C], "opengl", target_host=target_host, name="myadd") |
| |
| remote = rpc.connect(proxy_host, proxy_port, key="js") |
| |
| temp = util.tempdir() |
| ctx = remote.opengl(0) |
| path_obj = temp.relpath("myadd.bc") |
| path_dso = temp.relpath("myadd.js") |
| path_gl = temp.relpath("myadd.gl") |
| path_json = temp.relpath("myadd.tvm_meta.json") |
| |
| f.save(path_obj) |
| emscripten.create_js(path_dso, path_obj, side_module=True) |
| f.imported_modules[0].save(path_gl) |
| |
| remote.upload(path_dso, "myadd.dso") |
| remote.upload(path_gl) |
| remote.upload(path_json) |
| |
| remote.download("myadd.dso") |
| remote.download("myadd.gl") |
| remote.download("myadd.tvm_meta.json") |
| |
| print('Loading myadd.dso') |
| fhost = remote.load_module("myadd.dso") |
| |
| print('Loading myadd.gl') |
| fdev = remote.load_module("myadd.gl") |
| |
| print('import_module') |
| fhost.import_module(fdev) |
| |
| print('running...') |
| a = tvm.nd.array(np.random.uniform(size=16).astype(A.dtype), ctx) |
| b = tvm.nd.array(np.zeros(16, dtype=A.dtype), ctx) |
| c = tvm.nd.array(np.zeros(16, dtype=C.dtype), ctx) |
| fhost(a, b, c) |
| tvm.testing.assert_allclose(c.asnumpy(), a.asnumpy() + b.asnumpy()) |
| |
| if __name__ == "__main__": |
| try_remote_save_load() |