colin
/
onnx-mlir
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity
onnx-mlir/test/backend/test.py

336 lines
10 KiB
Python
Raw Normal View History

Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from __future__ import unicode_literals
import os
Enable e2e tests (#29) * Sync with latest MLIR. * Enable ONNX backend tests as a means to test ONNF lowering end-to-end. * Install ONNX using quiet mode. * Remove debug comments. * Install ONNX from third_party/onnx. * Check python version and fix pip command for installing ONNX. * Using --user install option to prevent permission denied. * Remove unused imports. * Try using stock ONNX pip package as there are more tests in them. * Pip got stuck building wheels, try sudo. * Use verbose install to debug. * Invalidate cache to build LLVM tools. * Fix mlir installation script location. * Debug to locate ONNF. * Sanity check. * Check out ONNF code first. * Use verbose LIT output. * 1. Update documentation to always use verbose LIT. 2. Update krnl ops to reflect new affine map attribute syntax. * See if conda exists * Install ONNX by manually cloning the repo. * Install cmake first. * Using sudo priviledge when installing. * Limit build parallelism. * Limit parallelism. * Larger memory. * Install onnx package with pip. * Build MLIR tools. * Invalidate cache. * Compile model.so with -fPIC. * Remove module dump to get concise debug output. * Print command before executing. * Use quiet install mode to reduce logging. * Use -relocation-model=pic to generate position independent code. * 1. Remove MAKEFLAGS because now buildbot has enough memory. 2. Run DocCheck as a last step. * 1. Add verbose mode for backtend test. * When dumping to LLVM bitcode, do not dump module IR, but print a message indicating that bitcode has been written to disk. * Do not pass MakeFlags to CMake. * Add more explaination for posible reasons of failing to identify tests.
2020-01-21 01:30:08 +08:00
import sys
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
import unittest
import onnx.backend.base
import onnx.backend.test
from onnx.backend.base import Device, DeviceType
import subprocess
Enable e2e tests (#29) * Sync with latest MLIR. * Enable ONNX backend tests as a means to test ONNF lowering end-to-end. * Install ONNX using quiet mode. * Remove debug comments. * Install ONNX from third_party/onnx. * Check python version and fix pip command for installing ONNX. * Using --user install option to prevent permission denied. * Remove unused imports. * Try using stock ONNX pip package as there are more tests in them. * Pip got stuck building wheels, try sudo. * Use verbose install to debug. * Invalidate cache to build LLVM tools. * Fix mlir installation script location. * Debug to locate ONNF. * Sanity check. * Check out ONNF code first. * Use verbose LIT output. * 1. Update documentation to always use verbose LIT. 2. Update krnl ops to reflect new affine map attribute syntax. * See if conda exists * Install ONNX by manually cloning the repo. * Install cmake first. * Using sudo priviledge when installing. * Limit build parallelism. * Limit parallelism. * Larger memory. * Install onnx package with pip. * Build MLIR tools. * Invalidate cache. * Compile model.so with -fPIC. * Remove module dump to get concise debug output. * Print command before executing. * Use quiet install mode to reduce logging. * Use -relocation-model=pic to generate position independent code. * 1. Remove MAKEFLAGS because now buildbot has enough memory. 2. Run DocCheck as a last step. * 1. Add verbose mode for backtend test. * When dumping to LLVM bitcode, do not dump module IR, but print a message indicating that bitcode has been written to disk. * Do not pass MakeFlags to CMake. * Add more explaination for posible reasons of failing to identify tests.
2020-01-21 01:30:08 +08:00
import test_config
VERBOSE = bool(os.environ.get("VERBOSE"))
CXX = test_config.CXX_PATH
ONNF = os.path.join(test_config.ONNF_BUILD_PATH, "bin/onnf")
LLC = os.path.join(test_config.LLVM_PROJ_BUILD_PATH, "bin/llc")
# Make lib folder under build directory visible in PYTHONPATH
doc_check_base_dir = os.path.dirname(os.path.realpath(__file__))
RUNTIME_DIR = os.path.join(test_config.ONNF_BUILD_PATH, "lib")
sys.path.append(RUNTIME_DIR)
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
from pyruntime import ExecutionSession
Enable e2e tests (#29) * Sync with latest MLIR. * Enable ONNX backend tests as a means to test ONNF lowering end-to-end. * Install ONNX using quiet mode. * Remove debug comments. * Install ONNX from third_party/onnx. * Check python version and fix pip command for installing ONNX. * Using --user install option to prevent permission denied. * Remove unused imports. * Try using stock ONNX pip package as there are more tests in them. * Pip got stuck building wheels, try sudo. * Use verbose install to debug. * Invalidate cache to build LLVM tools. * Fix mlir installation script location. * Debug to locate ONNF. * Sanity check. * Check out ONNF code first. * Use verbose LIT output. * 1. Update documentation to always use verbose LIT. 2. Update krnl ops to reflect new affine map attribute syntax. * See if conda exists * Install ONNX by manually cloning the repo. * Install cmake first. * Using sudo priviledge when installing. * Limit build parallelism. * Limit parallelism. * Larger memory. * Install onnx package with pip. * Build MLIR tools. * Invalidate cache. * Compile model.so with -fPIC. * Remove module dump to get concise debug output. * Print command before executing. * Use quiet install mode to reduce logging. * Use -relocation-model=pic to generate position independent code. * 1. Remove MAKEFLAGS because now buildbot has enough memory. 2. Run DocCheck as a last step. * 1. Add verbose mode for backtend test. * When dumping to LLVM bitcode, do not dump module IR, but print a message indicating that bitcode has been written to disk. * Do not pass MakeFlags to CMake. * Add more explaination for posible reasons of failing to identify tests.
2020-01-21 01:30:08 +08:00
def execute_commands(cmds):
if (VERBOSE):
print(" ".join(cmds))
subprocess.run(cmds, stdout=subprocess.PIPE)
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
class DummyBackend(onnx.backend.base.Backend):
@classmethod
Enable e2e tests (#29) * Sync with latest MLIR. * Enable ONNX backend tests as a means to test ONNF lowering end-to-end. * Install ONNX using quiet mode. * Remove debug comments. * Install ONNX from third_party/onnx. * Check python version and fix pip command for installing ONNX. * Using --user install option to prevent permission denied. * Remove unused imports. * Try using stock ONNX pip package as there are more tests in them. * Pip got stuck building wheels, try sudo. * Use verbose install to debug. * Invalidate cache to build LLVM tools. * Fix mlir installation script location. * Debug to locate ONNF. * Sanity check. * Check out ONNF code first. * Use verbose LIT output. * 1. Update documentation to always use verbose LIT. 2. Update krnl ops to reflect new affine map attribute syntax. * See if conda exists * Install ONNX by manually cloning the repo. * Install cmake first. * Using sudo priviledge when installing. * Limit build parallelism. * Limit parallelism. * Larger memory. * Install onnx package with pip. * Build MLIR tools. * Invalidate cache. * Compile model.so with -fPIC. * Remove module dump to get concise debug output. * Print command before executing. * Use quiet install mode to reduce logging. * Use -relocation-model=pic to generate position independent code. * 1. Remove MAKEFLAGS because now buildbot has enough memory. 2. Run DocCheck as a last step. * 1. Add verbose mode for backtend test. * When dumping to LLVM bitcode, do not dump module IR, but print a message indicating that bitcode has been written to disk. * Do not pass MakeFlags to CMake. * Add more explaination for posible reasons of failing to identify tests.
2020-01-21 01:30:08 +08:00
def prepare(cls, model, device='CPU', **kwargs):
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
super(DummyBackend, cls).prepare(model, device, **kwargs)
# Save model to disk as temp_model.onnx.
onnx.save(model, "temp_model.onnx")
# Call frontend to process temp_model.onnx, bit code will be generated.
Enable e2e tests (#29) * Sync with latest MLIR. * Enable ONNX backend tests as a means to test ONNF lowering end-to-end. * Install ONNX using quiet mode. * Remove debug comments. * Install ONNX from third_party/onnx. * Check python version and fix pip command for installing ONNX. * Using --user install option to prevent permission denied. * Remove unused imports. * Try using stock ONNX pip package as there are more tests in them. * Pip got stuck building wheels, try sudo. * Use verbose install to debug. * Invalidate cache to build LLVM tools. * Fix mlir installation script location. * Debug to locate ONNF. * Sanity check. * Check out ONNF code first. * Use verbose LIT output. * 1. Update documentation to always use verbose LIT. 2. Update krnl ops to reflect new affine map attribute syntax. * See if conda exists * Install ONNX by manually cloning the repo. * Install cmake first. * Using sudo priviledge when installing. * Limit build parallelism. * Limit parallelism. * Larger memory. * Install onnx package with pip. * Build MLIR tools. * Invalidate cache. * Compile model.so with -fPIC. * Remove module dump to get concise debug output. * Print command before executing. * Use quiet install mode to reduce logging. * Use -relocation-model=pic to generate position independent code. * 1. Remove MAKEFLAGS because now buildbot has enough memory. 2. Run DocCheck as a last step. * 1. Add verbose mode for backtend test. * When dumping to LLVM bitcode, do not dump module IR, but print a message indicating that bitcode has been written to disk. * Do not pass MakeFlags to CMake. * Add more explaination for posible reasons of failing to identify tests.
2020-01-21 01:30:08 +08:00
execute_commands([ONNF, "temp_model.onnx"])
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
# Call llc to generate object file from bitcode.
Enable e2e tests (#29) * Sync with latest MLIR. * Enable ONNX backend tests as a means to test ONNF lowering end-to-end. * Install ONNX using quiet mode. * Remove debug comments. * Install ONNX from third_party/onnx. * Check python version and fix pip command for installing ONNX. * Using --user install option to prevent permission denied. * Remove unused imports. * Try using stock ONNX pip package as there are more tests in them. * Pip got stuck building wheels, try sudo. * Use verbose install to debug. * Invalidate cache to build LLVM tools. * Fix mlir installation script location. * Debug to locate ONNF. * Sanity check. * Check out ONNF code first. * Use verbose LIT output. * 1. Update documentation to always use verbose LIT. 2. Update krnl ops to reflect new affine map attribute syntax. * See if conda exists * Install ONNX by manually cloning the repo. * Install cmake first. * Using sudo priviledge when installing. * Limit build parallelism. * Limit parallelism. * Larger memory. * Install onnx package with pip. * Build MLIR tools. * Invalidate cache. * Compile model.so with -fPIC. * Remove module dump to get concise debug output. * Print command before executing. * Use quiet install mode to reduce logging. * Use -relocation-model=pic to generate position independent code. * 1. Remove MAKEFLAGS because now buildbot has enough memory. 2. Run DocCheck as a last step. * 1. Add verbose mode for backtend test. * When dumping to LLVM bitcode, do not dump module IR, but print a message indicating that bitcode has been written to disk. * Do not pass MakeFlags to CMake. * Add more explaination for posible reasons of failing to identify tests.
2020-01-21 01:30:08 +08:00
execute_commands(
[LLC, "-filetype=obj", "-relocation-model=pic", "model.bc"])
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
# Generate shared library from object file, linking with c runtime.
Enable e2e tests (#29) * Sync with latest MLIR. * Enable ONNX backend tests as a means to test ONNF lowering end-to-end. * Install ONNX using quiet mode. * Remove debug comments. * Install ONNX from third_party/onnx. * Check python version and fix pip command for installing ONNX. * Using --user install option to prevent permission denied. * Remove unused imports. * Try using stock ONNX pip package as there are more tests in them. * Pip got stuck building wheels, try sudo. * Use verbose install to debug. * Invalidate cache to build LLVM tools. * Fix mlir installation script location. * Debug to locate ONNF. * Sanity check. * Check out ONNF code first. * Use verbose LIT output. * 1. Update documentation to always use verbose LIT. 2. Update krnl ops to reflect new affine map attribute syntax. * See if conda exists * Install ONNX by manually cloning the repo. * Install cmake first. * Using sudo priviledge when installing. * Limit build parallelism. * Limit parallelism. * Larger memory. * Install onnx package with pip. * Build MLIR tools. * Invalidate cache. * Compile model.so with -fPIC. * Remove module dump to get concise debug output. * Print command before executing. * Use quiet install mode to reduce logging. * Use -relocation-model=pic to generate position independent code. * 1. Remove MAKEFLAGS because now buildbot has enough memory. 2. Run DocCheck as a last step. * 1. Add verbose mode for backtend test. * When dumping to LLVM bitcode, do not dump module IR, but print a message indicating that bitcode has been written to disk. * Do not pass MakeFlags to CMake. * Add more explaination for posible reasons of failing to identify tests.
2020-01-21 01:30:08 +08:00
execute_commands([
CXX, "-shared", "-fPIC", "model.o", "-o", "model.so",
"-L" + RUNTIME_DIR, "-lcruntime"
])
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
return ExecutionSession("./model.so", "_dyn_entry_point_main_graph")
@classmethod
def supports_device(cls, device):
d = Device(device)
if d.type == DeviceType.CPU:
return True
return False
backend_test = onnx.backend.test.BackendTest(DummyBackend, __name__)
# Test directories:
# https://github.com/onnx/onnx/tree/master/onnx/backend/test/data/node
test_to_enable = [
# Add Op:
"test_add_cpu",
"test_add_bcast_cpu",
# And Op:
# Sub Op:
"test_sub_cpu",
"test_sub_bcast_cpu",
"test_sub_example_cpu",
# Cosh Op:
"test_cosh_cpu",
"test_cosh_example_cpu",
# Div Op:
"test_div_cpu",
"test_div_bcast_cpu",
"test_div_example_cpu",
# Elu Op:
"test_elu_cpu",
"test_elu_default_cpu",
"test_elu_example_cpu",
# Exp Op:
"test_exp_cpu",
"test_exp_example_cpu",
Lowering Gemm (#19) * Initial implementation * Support transposing inputs * Revise unidirectional broadcasting and unknown dimensions * Revise gemm * Add testcase * Rename some variables * Update SharingWork.md * Change from the use of Value* to Value * Insert deallocation * Initilize the output matrix and fix wrong computation * Add end-to-end testcases * Edit lowering tests * Change attribute names * Use emplace_push for SmallVector * Use the new way of getting attributes * Revise the use of attributes * Check the bias's shape Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-01-30 00:11:49 +08:00
# Gemm Op:
"test_gemm_all_attributes_cpu",
"test_gemm_alpha_cpu",
"test_gemm_beta_cpu",
"test_gemm_default_matrix_bias_cpu",
Add support of GemmNoBias (#91) * Add support of GemmNoBias * Fix a wrong indentation
2020-02-20 23:55:24 +08:00
"test_gemm_default_no_bias_cpu",
Fix scalar entry point parameter lowering issue. (#78) * Fix scalar entry point parameter lowering issue. * Enable scalar bias test. * Nit. Improve comments and remove debug code. * Make helper function static, move to upfront position. * Move helper function to top of the file. Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-02-13 13:50:05 +08:00
"test_gemm_default_scalar_bias_cpu",
Lowering Gemm (#19) * Initial implementation * Support transposing inputs * Revise unidirectional broadcasting and unknown dimensions * Revise gemm * Add testcase * Rename some variables * Update SharingWork.md * Change from the use of Value* to Value * Insert deallocation * Initilize the output matrix and fix wrong computation * Add end-to-end testcases * Edit lowering tests * Change attribute names * Use emplace_push for SmallVector * Use the new way of getting attributes * Revise the use of attributes * Check the bias's shape Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-01-30 00:11:49 +08:00
"test_gemm_default_single_elem_vector_bias_cpu",
"test_gemm_default_vector_bias_cpu",
"test_gemm_default_zero_bias_cpu",
"test_gemm_transposeA_cpu",
"test_gemm_transposeB_cpu",
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
# Hard Sigmoid Op:
"test_hardsigmoid_cpu",
"test_hardsigmoid_default_cpu",
"test_hardsigmoid_example_cpu",
# Leaky Relu Op:
"test_leakyrelu_cpu",
"test_leakyrelu_default_cpu",
"test_leakyrelu_example_cpu",
# Max Op:
Allow importing variadic inputs/outputs of onnx operators (#16) * Allow importing variadic inputs/outputs of onnx operators * Enable testcases for variadic ops * Modify gen_doc.py
2020-01-28 21:48:11 +08:00
"test_max_example_cpu",
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
"test_max_one_input_cpu",
Allow importing variadic inputs/outputs of onnx operators (#16) * Allow importing variadic inputs/outputs of onnx operators * Enable testcases for variadic ops * Modify gen_doc.py
2020-01-28 21:48:11 +08:00
"test_max_two_inputs_cpu",
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
# Min Op:
Allow importing variadic inputs/outputs of onnx operators (#16) * Allow importing variadic inputs/outputs of onnx operators * Enable testcases for variadic ops * Modify gen_doc.py
2020-01-28 21:48:11 +08:00
"test_min_example_cpu",
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
"test_min_one_input_cpu",
Allow importing variadic inputs/outputs of onnx operators (#16) * Allow importing variadic inputs/outputs of onnx operators * Enable testcases for variadic ops * Modify gen_doc.py
2020-01-28 21:48:11 +08:00
"test_min_two_inputs_cpu",
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
# Mul Op:
"test_mul_cpu",
"test_mul_bcast_cpu",
"test_mul_example_cpu",
# Relu Op:
"test_relu_cpu",
Lowering ReductionMax, ReductionMin, ReductionProd and ReductionSum (#31) * Shape inference for reduction * Lower ReduceSum * Support list-like attributes * Add ReduceMax, ReduceMin, ReduceProd * Add tests * Emit errors for unsupported types * Typos * Add backend test * Fix axis computation * Update the use of attributes * Use SmallVector * Address stylistic comments * Change type from int to int64_t for indices * Change type from int to int64_t for indices
2020-02-10 21:38:19 +08:00
# ReduceMax Op:
"test_reduce_max_default_axes_keepdim_example_cpu",
"test_reduce_max_default_axes_keepdims_random_cpu",
"test_reduce_max_do_not_keepdims_example_cpu",
"test_reduce_max_do_not_keepdims_random_cpu",
"test_reduce_max_keepdims_example_cpu",
"test_reduce_max_keepdims_random_cpu",
"test_reduce_max_negative_axes_keepdims_example_cpu",
"test_reduce_max_negative_axes_keepdims_random_cpu",
# ReduceMin Op:
"test_reduce_min_default_axes_keepdims_example_cpu",
"test_reduce_min_default_axes_keepdims_random_cpu",
"test_reduce_min_do_not_keepdims_example_cpu",
"test_reduce_min_do_not_keepdims_random_cpu",
"test_reduce_min_keepdims_example_cpu",
"test_reduce_min_keepdims_random_cpu",
"test_reduce_min_negative_axes_keepdims_example_cpu",
"test_reduce_min_negative_axes_keepdims_random_cpu",
# ReduceProd Op:
"test_reduce_prod_default_axes_keepdims_example_cpu",
"test_reduce_prod_default_axes_keepdims_random_cpu",
"test_reduce_prod_do_not_keepdims_example_cpu",
"test_reduce_prod_do_not_keepdims_random_cpu",
"test_reduce_prod_keepdims_example_cpu",
"test_reduce_prod_keepdims_random_cpu",
"test_reduce_prod_negative_axes_keepdims_example_cpu",
"test_reduce_prod_negative_axes_keepdims_random_cpu",
# ReduceSum Op:
"test_reduce_sum_default_axes_keepdims_example_cpu",
"test_reduce_sum_default_axes_keepdims_random_cpu",
"test_reduce_sum_do_not_keepdims_example_cpu",
"test_reduce_sum_do_not_keepdims_random_cpu",
"test_reduce_sum_keepdims_example_cpu",
"test_reduce_sum_keepdims_random_cpu",
"test_reduce_sum_negative_axes_keepdims_example_cpu",
"test_reduce_sum_negative_axes_keepdims_random_cpu",
Add e2e tests related to Reduction Ops (#79)
2020-02-12 16:40:32 +08:00
# ReduceL1: this op depends on ONNXAbsOp so we will turn these tests on once ONNXAbsOp is implemented.
#"test_reduce_l1_default_axes_keepdims_example_cpu",
#"test_reduce_l1_default_axes_keepdims_random_cpu",
#"test_reduce_l1_do_not_keepdims_example_cpu",
#"test_reduce_l1_do_not_keepdims_random_cpu",
#"test_reduce_l1_keep_dims_example_cpu",
#"test_reduce_l1_keep_dims_random_cpu",
#"test_reduce_l1_negative_axes_keep_dims_example_cpu",
#"test_reduce_l1_negative_axes_keep_dims_random_cpu",
# ReduceL2
"test_reduce_l2_default_axes_keepdims_example_cpu",
"test_reduce_l2_default_axes_keepdims_random_cpu",
"test_reduce_l2_do_not_keepdims_example_cpu",
"test_reduce_l2_do_not_keepdims_random_cpu",
"test_reduce_l2_keep_dims_example_cpu",
"test_reduce_l2_keep_dims_random_cpu",
"test_reduce_l2_negative_axes_keep_dims_example_cpu",
"test_reduce_l2_negative_axes_keep_dims_random_cpu",
# ReduceLogSum
"test_reduce_log_sum_asc_axes_cpu",
"test_reduce_log_sum_cpu",
"test_reduce_log_sum_default_cpu",
"test_reduce_log_sum_desc_axes_cpu",
# ReduceLogSumExp
"test_reduce_log_sum_exp_default_axes_keepdims_example_cpu",
"test_reduce_log_sum_exp_default_axes_keepdims_random_cpu",
"test_reduce_log_sum_exp_do_not_keepdims_example_cpu",
"test_reduce_log_sum_exp_do_not_keepdims_random_cpu",
"test_reduce_log_sum_exp_keepdims_example_cpu",
"test_reduce_log_sum_exp_keepdims_random_cpu",
"test_reduce_log_sum_exp_negative_axes_keepdims_example_cpu",
"test_reduce_log_sum_exp_negative_axes_keepdims_random_cpu",
"test_reduce_log_sum_negative_axes_cpu",
# ReduceSumSquare
"test_reduce_sum_square_default_axes_keepdims_example_cpu",
"test_reduce_sum_square_default_axes_keepdims_random_cpu",
"test_reduce_sum_square_do_not_keepdims_example_cpu",
"test_reduce_sum_square_do_not_keepdims_random_cpu",
"test_reduce_sum_square_keepdims_example_cpu",
"test_reduce_sum_square_keepdims_random_cpu",
"test_reduce_sum_square_negative_axes_keepdims_example_cpu",
"test_reduce_sum_square_negative_axes_keepdims_random_cpu",
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
# Selu Op:
"test_selu_cpu",
"test_selu_default_cpu",
"test_selu_example_cpu",
# Sigmoid Op:
"test_sigmoid_cpu",
"test_sigmoid_example_cpu",
Enable e2e tests (#29) * Sync with latest MLIR. * Enable ONNX backend tests as a means to test ONNF lowering end-to-end. * Install ONNX using quiet mode. * Remove debug comments. * Install ONNX from third_party/onnx. * Check python version and fix pip command for installing ONNX. * Using --user install option to prevent permission denied. * Remove unused imports. * Try using stock ONNX pip package as there are more tests in them. * Pip got stuck building wheels, try sudo. * Use verbose install to debug. * Invalidate cache to build LLVM tools. * Fix mlir installation script location. * Debug to locate ONNF. * Sanity check. * Check out ONNF code first. * Use verbose LIT output. * 1. Update documentation to always use verbose LIT. 2. Update krnl ops to reflect new affine map attribute syntax. * See if conda exists * Install ONNX by manually cloning the repo. * Install cmake first. * Using sudo priviledge when installing. * Limit build parallelism. * Limit parallelism. * Larger memory. * Install onnx package with pip. * Build MLIR tools. * Invalidate cache. * Compile model.so with -fPIC. * Remove module dump to get concise debug output. * Print command before executing. * Use quiet install mode to reduce logging. * Use -relocation-model=pic to generate position independent code. * 1. Remove MAKEFLAGS because now buildbot has enough memory. 2. Run DocCheck as a last step. * 1. Add verbose mode for backtend test. * When dumping to LLVM bitcode, do not dump module IR, but print a message indicating that bitcode has been written to disk. * Do not pass MakeFlags to CMake. * Add more explaination for posible reasons of failing to identify tests.
2020-01-21 01:30:08 +08:00
Lowering softmax (#14) * Rebase * Use max normalization * Handle axis * Add tests * Update SharingWork.md * Remove redundant spaces * Format code * Rebase * Change from the use of Value* to Value * Add end-to-end tests Co-authored-by: Tian Jin <tjingrant@gmail.com>
2020-01-21 10:57:32 +08:00
# Softmax Op:
"test_softmax_axis_0_cpu",
"test_softmax_axis_1_cpu",
"test_softmax_axis_2_cpu",
"test_softmax_default_axis_cpu",
"test_softmax_example_cpu",
"test_softmax_large_number_cpu",
Add KrnlSqrtOp (#22) * Initial lowering of KrnlSqrtOp * Fix errors and add a testcase * typos * Add the MLIR example * Restore doc/doc_check/CMakeLists.txt * Clean the code * Edit comments * Remove redundant parts * Chang the use of -> to . * Add a test for f64 * Support ONNXSqrtOp * Fix indentation Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-01-29 00:10:47 +08:00
# Sqrt Op:
"test_sqrt_cpu",
"test_sqrt_example_cpu",
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
# Sum Op:
Allow importing variadic inputs/outputs of onnx operators (#16) * Allow importing variadic inputs/outputs of onnx operators * Enable testcases for variadic ops * Modify gen_doc.py
2020-01-28 21:48:11 +08:00
"test_sum_example_cpu",
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
"test_sum_one_input_cpu",
Allow importing variadic inputs/outputs of onnx operators (#16) * Allow importing variadic inputs/outputs of onnx operators * Enable testcases for variadic ops * Modify gen_doc.py
2020-01-28 21:48:11 +08:00
"test_sum_two_inputs_cpu",
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
Add support for Unsqueeze (#50) * Infer shape for Unsqueeze * Lower Unsqueeze * Revise * Turn off backend tests * Compute tensorSize for static shape * Compute tensorSize with unknown dims * Edit tests * Update the use of attributes * Add e2e tests * Use SmallVector * Remove return * Check whether the operand is ranked or not Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-01-29 23:46:02 +08:00
# Unsqueeze Op:
"test_unsqueeze_axis_0_cpu",
"test_unsqueeze_axis_1_cpu",
"test_unsqueeze_axis_2_cpu",
"test_unsqueeze_axis_3_cpu",
"test_unsqueeze_negative_axes_cpu",
"test_unsqueeze_three_axes_cpu",
"test_unsqueeze_two_axes_cpu",
Lower transpose operation to KRNL dialect (#54) * Lower transpose operation. * Fix IndetityOp. * Add tests. * Add backend tests. * Clean-up code. * Move transpose code and improve comment.
2020-01-31 00:44:56 +08:00
# "test_unsqueeze_unsorted_axes_cpu",
Add support for Unsqueeze (#50) * Infer shape for Unsqueeze * Lower Unsqueeze * Revise * Turn off backend tests * Compute tensorSize for static shape * Compute tensorSize with unknown dims * Edit tests * Update the use of attributes * Add e2e tests * Use SmallVector * Remove return * Check whether the operand is ranked or not Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-01-29 23:46:02 +08:00
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
# Reciprocal Op:
Re-enable Reciprocal tests.
2020-01-22 10:41:22 +08:00
"test_reciprocal_cpu",
"test_reciprocal_example_cpu",
Support Softplus and Softsign operations (#17) * Support Softplus and Softsign operations * Add the default shape inference for the transposition operation. * Fix conflict with master * Fix conflict with master branch * Add test for softplus and softsign in test/backend/test.py * Re-enable Reciprocal tests. Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com> Co-authored-by: Tian Jin <tjingrant@gmail.com>
2020-01-24 12:18:38 +08:00
# SoftplusOp:
"test_softplus_cpu",
"test_softplus_example_cpu",
# SoftsignOp:
"test_softsign_cpu",
"test_softsign_example_cpu",
Fix reshape op. (#53)
2020-01-28 23:21:08 +08:00
# ReshapeOp:
Support dimension zero in reshape (#55) Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-01-29 23:41:09 +08:00
"test_reshape_extended_dims_cpu",
Add support of negative dimensions (#66) Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-02-11 23:37:47 +08:00
"test_reshape_negative_dim_cpu",
"test_reshape_negative_extended_dims_cpu",
Support dimension zero in reshape (#55) Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-01-29 23:41:09 +08:00
"test_reshape_one_dim_cpu",
"test_reshape_reduced_dims_cpu",
Fix reshape op. (#53)
2020-01-28 23:21:08 +08:00
"test_reshape_reordered_all_dims_cpu",
Support dimension zero in reshape (#55) Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-01-29 23:41:09 +08:00
"test_reshape_reordered_last_dims_cpu",
Add support of negative dimensions (#66) Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-02-11 23:37:47 +08:00
"test_reshape_zero_and_negative_dim_cpu",
Support dimension zero in reshape (#55) Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-01-29 23:41:09 +08:00
"test_reshape_zero_dim_cpu",
Lower transpose operation to KRNL dialect (#54) * Lower transpose operation. * Fix IndetityOp. * Add tests. * Add backend tests. * Clean-up code. * Move transpose code and improve comment.
2020-01-31 00:44:56 +08:00
# Transpose
"test_transpose_default_cpu",
"test_transpose_all_permutations_0_cpu",
"test_transpose_all_permutations_1_cpu",
"test_transpose_all_permutations_2_cpu",
"test_transpose_all_permutations_3_cpu",
"test_transpose_all_permutations_4_cpu",
"test_transpose_all_permutations_5_cpu",
Added lowering of SignOp (#21) * Support lowering of SignOp * Fixed test code for signop of integer input * Inserted Sigh and Reciprocal in SharingWork.md (Reciprocal is for past commit 7e3f96e) * Added test for Sign Op * Fixed minus_one -> minusOne * Fixed test for signop
2020-02-04 22:27:17 +08:00
Lower convolution to KRNL dialect. (#65) * Ensure data shape is at least 4. * First version of convolution. * Simplify code for KRNL lowering. * Add test without padding or strides. * Refactor code for lowering frontend operations to KRNL dialect. * Add test for conv with no bias and no padding. * Add test with group greater than one. * Address comment.
2020-02-08 05:51:32 +08:00
# Conv
"test_basic_conv_without_padding_cpu",
Add support for strides when emitting convolution loop nest. (#76) * Add support for strides when emitting convolution loop nest. * Only emit stride multiplication if strides is greater than one. * Add test.
2020-02-12 00:53:13 +08:00
"test_conv_with_strides_no_padding_cpu",
Lower convolution to KRNL dialect. (#65) * Ensure data shape is at least 4. * First version of convolution. * Simplify code for KRNL lowering. * Add test without padding or strides. * Refactor code for lowering frontend operations to KRNL dialect. * Add test for conv with no bias and no padding. * Add test with group greater than one. * Address comment.
2020-02-08 05:51:32 +08:00
Added lowering of SignOp (#21) * Support lowering of SignOp * Fixed test code for signop of integer input * Inserted Sigh and Reciprocal in SharingWork.md (Reciprocal is for past commit 7e3f96e) * Added test for Sign Op * Fixed minus_one -> minusOne * Fixed test for signop
2020-02-04 22:27:17 +08:00
# Sign Op:
"test_sign_cpu",
Lower Matmul operation to Krnl dialect (#57) * Allocate memory for matmul's result * Group cases * Add support of N-D x N-D, N>=2 * Revise createIterateOperandPack * Add 1-D x 1-D * Add 1-D x N-D * Add MLIR tests * Change variable names * Change type from int to int64_t for indices * Change variable names * Change int64_t back to int * Change int64_t back to int * Change int64_t back to int * Use decltype Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com> Co-authored-by: Tian Jin <tjingrant@gmail.com>
2020-02-14 23:43:17 +08:00
# MatmulOp
"test_matmul_2d_cpu",
"test_matmul_3d_cpu",
"test_matmul_4d_cpu",
Lower BatchNormalization (test mode) to Krnl dialect (#70) * Add ONNXBatchNormalizationTestModeOp and its shape inference * Lower batchnormalization test mode * re-use scale, bias, mean, and variance * Add MLIR tests * Add e2e tests * fix typos * Fix a bug in MLIR tests * Change type from int to int64_t for indices * Uncomment e2e tests due to segmentation fault * Uncomment e2e tests due to segmentation fault * Revise the code * [Tian] Fix segmentation fault in e2e tests * Re-generate onnx.md to include BatchNormalizationTestModeOp * Reverse an unintentional change * Fix some typos in comments * Use convertToMemRefType from the master branch Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-02-21 00:45:40 +08:00
# BatchNormalization (test mode)
"test_batchnorm_epsilon_cpu",
"test_batchnorm_example_cpu",
Lower MaxPoolSingleOutOp to Krnl dialect (#1) * Lower MaxPoolSingleOutOp to Krnl dialect * Edit comments * Update changes according to the new folder structure * Add MLIR tests * Support ceil_mode * Merge the first two krnl loops into one krnl loop; remove attribute checks * Dynamically allocate memory for the result if the result has unknown dimensions Co-authored-by: Gheorghe-Teodor Bercea <gt.bercea@gmail.com>
2020-03-05 03:27:21 +08:00
# Pooling
"test_maxpool_1d_default_cpu",
"test_maxpool_2d_ceil_cpu",
"test_maxpool_2d_default_cpu",
"test_maxpool_2d_strides_cpu",
"test_maxpool_3d_default_cpu",
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
]
# Extract name of all test cases.
import inspect
all_tests = inspect.getmembers(
backend_test.test_cases["OnnxBackendNodeModelTest"])
all_test_names = list(map(lambda x: x[0], all_tests))
Enable e2e tests (#29) * Sync with latest MLIR. * Enable ONNX backend tests as a means to test ONNF lowering end-to-end. * Install ONNX using quiet mode. * Remove debug comments. * Install ONNX from third_party/onnx. * Check python version and fix pip command for installing ONNX. * Using --user install option to prevent permission denied. * Remove unused imports. * Try using stock ONNX pip package as there are more tests in them. * Pip got stuck building wheels, try sudo. * Use verbose install to debug. * Invalidate cache to build LLVM tools. * Fix mlir installation script location. * Debug to locate ONNF. * Sanity check. * Check out ONNF code first. * Use verbose LIT output. * 1. Update documentation to always use verbose LIT. 2. Update krnl ops to reflect new affine map attribute syntax. * See if conda exists * Install ONNX by manually cloning the repo. * Install cmake first. * Using sudo priviledge when installing. * Limit build parallelism. * Limit parallelism. * Larger memory. * Install onnx package with pip. * Build MLIR tools. * Invalidate cache. * Compile model.so with -fPIC. * Remove module dump to get concise debug output. * Print command before executing. * Use quiet install mode to reduce logging. * Use -relocation-model=pic to generate position independent code. * 1. Remove MAKEFLAGS because now buildbot has enough memory. 2. Run DocCheck as a last step. * 1. Add verbose mode for backtend test. * When dumping to LLVM bitcode, do not dump module IR, but print a message indicating that bitcode has been written to disk. * Do not pass MakeFlags to CMake. * Add more explaination for posible reasons of failing to identify tests.
2020-01-21 01:30:08 +08:00
# Ensure that test names specified in test_to_enable actually exist.
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
for test_name in test_to_enable:
Lower transpose operation to KRNL dialect (#54) * Lower transpose operation. * Fix IndetityOp. * Add tests. * Add backend tests. * Clean-up code. * Move transpose code and improve comment.
2020-01-31 00:44:56 +08:00
assert test_name in all_test_names, """test name {} not found, it is likely
that you may have misspelled the test name or the specified test does not
exist in the version of onnx package you installed.""".format(
Enable e2e tests (#29) * Sync with latest MLIR. * Enable ONNX backend tests as a means to test ONNF lowering end-to-end. * Install ONNX using quiet mode. * Remove debug comments. * Install ONNX from third_party/onnx. * Check python version and fix pip command for installing ONNX. * Using --user install option to prevent permission denied. * Remove unused imports. * Try using stock ONNX pip package as there are more tests in them. * Pip got stuck building wheels, try sudo. * Use verbose install to debug. * Invalidate cache to build LLVM tools. * Fix mlir installation script location. * Debug to locate ONNF. * Sanity check. * Check out ONNF code first. * Use verbose LIT output. * 1. Update documentation to always use verbose LIT. 2. Update krnl ops to reflect new affine map attribute syntax. * See if conda exists * Install ONNX by manually cloning the repo. * Install cmake first. * Using sudo priviledge when installing. * Limit build parallelism. * Limit parallelism. * Larger memory. * Install onnx package with pip. * Build MLIR tools. * Invalidate cache. * Compile model.so with -fPIC. * Remove module dump to get concise debug output. * Print command before executing. * Use quiet install mode to reduce logging. * Use -relocation-model=pic to generate position independent code. * 1. Remove MAKEFLAGS because now buildbot has enough memory. 2. Run DocCheck as a last step. * 1. Add verbose mode for backtend test. * When dumping to LLVM bitcode, do not dump module IR, but print a message indicating that bitcode has been written to disk. * Do not pass MakeFlags to CMake. * Add more explaination for posible reasons of failing to identify tests.
2020-01-21 01:30:08 +08:00
test_name)
Enable ONNX Backend Test (#1) * wip, commit before merging with upstream * organize API, return wrapped output * enable onnx backend test * undo unintentional commit * fix krnl ops tablegen * format krnl ops * reorder fillDynMemRefWithMemRef to be after fillPtrToMemRefWithDynMemRef, better comments * more onnx backend tests * ensure that test names refer to existing tests * improve code readability by shortening type names * nit * restore unintentional changes * more nits * fix ; -> : * split runtime implementation into header and body file, add support for data types * comment on the onnx backend test * make the comments read better * do not dump when lowering
2019-12-22 13:25:02 +08:00
backend_test.include(r"^{}$".format(test_name))
# import all test cases at global scope to make them visible to python.unittest
globals().update(backend_test.test_cases)
if __name__ == '__main__':
unittest.main()