From 9248e159c9e61c179c3825ab0c271782d6ca0c58 Mon Sep 17 00:00:00 2001 From: shoubhik Date: Sat, 18 Apr 2020 21:09:32 -0700 Subject: [PATCH] Remove developer facing api from frontend exports. (#5375) --- python/tvm/relay/frontend/__init__.py | 4 -- .../frontend/mxnet/test_qnn_ops_utils.py | 37 ++++++++++--------- 2 files changed, 19 insertions(+), 22 deletions(-) diff --git a/python/tvm/relay/frontend/__init__.py b/python/tvm/relay/frontend/__init__.py index fa258f48ac76..aba9eea494be 100644 --- a/python/tvm/relay/frontend/__init__.py +++ b/python/tvm/relay/frontend/__init__.py @@ -24,10 +24,6 @@ from __future__ import absolute_import from .mxnet import from_mxnet -from .mxnet_qnn_op_utils import dequantize_mxnet_min_max -from .mxnet_qnn_op_utils import quantize_mxnet_min_max -from .mxnet_qnn_op_utils import get_mkldnn_int8_scale -from .mxnet_qnn_op_utils import get_mkldnn_uint8_scale from .mxnet_qnn_op_utils import quantize_conv_bias_mkldnn_from_var from .keras import from_keras from .onnx import from_onnx diff --git a/tests/python/frontend/mxnet/test_qnn_ops_utils.py b/tests/python/frontend/mxnet/test_qnn_ops_utils.py index 32042562b209..d130eef3b962 100644 --- a/tests/python/frontend/mxnet/test_qnn_ops_utils.py +++ b/tests/python/frontend/mxnet/test_qnn_ops_utils.py @@ -16,10 +16,14 @@ # under the License. import tvm -from tvm import te import numpy as np from tvm import relay from tvm.contrib import graph_runtime +from tvm.relay.frontend.mxnet_qnn_op_utils import dequantize_mxnet_min_max, \ + quantize_mxnet_min_max, \ + get_mkldnn_int8_scale, \ + get_mkldnn_uint8_scale, \ + quantize_conv_bias_mkldnn_from_var def test_mkldnn_dequantize(): @@ -29,11 +33,10 @@ def dequantize_test_driver(in_dtype, quant_args, in_data, verify_output_data): input_data = relay.var("input_data", shape=shape, dtype=in_dtype) min_range = quant_args['min_range'] max_range = quant_args['max_range'] - dequantized_output = \ - relay.frontend.dequantize_mxnet_min_max(input_data, - min_range=min_range, - max_range=max_range, - in_dtype=in_dtype) + dequantized_output = dequantize_mxnet_min_max(input_data, + min_range=min_range, + max_range=max_range, + in_dtype=in_dtype) mod = relay.Function(relay.analysis.free_vars(dequantized_output), dequantized_output) mod = tvm.IRModule.from_expr(mod) with relay.build_config(opt_level=3): @@ -79,17 +82,15 @@ def test_int8_to_float32(): def test_mkldnn_quantize(): - def quantize_test_driver(out_dtype, quant_args, in_data, verify_output_data): shape = in_data.shape input_data = relay.var("input_data", shape=shape, dtype='float32') min_range = quant_args['min_range'] max_range = quant_args['max_range'] - quantized_output, _, _ = \ - relay.frontend.quantize_mxnet_min_max(input_data, - min_range=min_range, - max_range=max_range, - out_dtype=out_dtype) + quantized_output, _, _ = quantize_mxnet_min_max(input_data, + min_range=min_range, + max_range=max_range, + out_dtype=out_dtype) mod = relay.Function(relay.analysis.free_vars(quantized_output), quantized_output) mod = tvm.IRModule.from_expr(mod) with relay.build_config(opt_level=3): @@ -140,8 +141,8 @@ def test_get_mkldnn_int8_scale(): range_min = -3.904039 range_max = 3.904039 expected = 0.03061991354976495 - output = relay.frontend.get_mkldnn_int8_scale(range_max=range_max, - range_min=range_min) + output = get_mkldnn_int8_scale(range_max=range_max, + range_min=range_min) assert np.allclose(output, expected) @@ -149,15 +150,15 @@ def test_get_mkldnn_uint8_scale(): range_min = 0.0 range_max = 55.77269 expected = 0.21828841189047482 - output = relay.frontend.get_mkldnn_uint8_scale(range_max=range_max, - range_min=range_min) + output = get_mkldnn_uint8_scale(range_max=range_max, + range_min=range_min) assert np.allclose(output, expected) def test_quantize_conv_bias_mkldnn_from_var(): bias_var = relay.var('bias', shape=(3,), dtype='float32') bias_scale = tvm.nd.array(np.array([0.5, 0.6, 0.7])) - output = relay.frontend.quantize_conv_bias_mkldnn_from_var(bias_var, bias_scale) + output = quantize_conv_bias_mkldnn_from_var(bias_var, bias_scale) assert isinstance(output, tvm.relay.expr.Call) attrs = output.attrs assert attrs.axis == 0 @@ -171,4 +172,4 @@ def test_quantize_conv_bias_mkldnn_from_var(): test_mkldnn_quantize() test_get_mkldnn_int8_scale() test_get_mkldnn_uint8_scale() - test_quantize_conv_bias_mkldnn_from_var() \ No newline at end of file + test_quantize_conv_bias_mkldnn_from_var()