mirror of
https://github.com/zama-ai/concrete.git
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314 lines
11 KiB
Python
314 lines
11 KiB
Python
"""Test file for debugging functions"""
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import numpy
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import pytest
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from concrete.common.data_types.integers import Integer
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from concrete.common.debugging import draw_graph, get_printable_graph
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from concrete.common.extensions.table import LookupTable
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from concrete.common.values import ClearScalar, EncryptedScalar, EncryptedTensor
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from concrete.numpy import tracing
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LOOKUP_TABLE_FROM_2B_TO_4B = LookupTable([9, 2, 4, 11])
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LOOKUP_TABLE_FROM_3B_TO_2B = LookupTable([0, 1, 3, 2, 2, 3, 1, 0])
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def issue_130_a(x, y):
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"""Test case derived from issue #130"""
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# pylint: disable=unused-argument
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intermediate = x + 1
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return (intermediate, intermediate)
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# pylint: enable=unused-argument
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def issue_130_b(x, y):
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"""Test case derived from issue #130"""
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# pylint: disable=unused-argument
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intermediate = x - 1
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return (intermediate, intermediate)
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# pylint: enable=unused-argument
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def issue_130_c(x, y):
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"""Test case derived from issue #130"""
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# pylint: disable=unused-argument
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intermediate = 1 - x
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return (intermediate, intermediate)
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# pylint: enable=unused-argument
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@pytest.mark.parametrize(
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"lambda_f,ref_graph_str",
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[
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(lambda x, y: x + y, "%0 = x\n%1 = y\n%2 = Add(0, 1)\nreturn(%2)\n"),
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(lambda x, y: x - y, "%0 = x\n%1 = y\n%2 = Sub(0, 1)\nreturn(%2)\n"),
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(lambda x, y: x + x, "%0 = x\n%1 = Add(0, 0)\nreturn(%1)\n"),
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(
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lambda x, y: x + x - y * y * y + x,
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"%0 = x\n%1 = y\n%2 = Add(0, 0)\n%3 = Mul(1, 1)"
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"\n%4 = Mul(3, 1)\n%5 = Sub(2, 4)\n%6 = Add(5, 0)\nreturn(%6)\n",
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),
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(lambda x, y: x + 1, "%0 = x\n%1 = Constant(1)\n%2 = Add(0, 1)\nreturn(%2)\n"),
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(lambda x, y: 1 + x, "%0 = x\n%1 = Constant(1)\n%2 = Add(0, 1)\nreturn(%2)\n"),
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(lambda x, y: (-1) + x, "%0 = x\n%1 = Constant(-1)\n%2 = Add(0, 1)\nreturn(%2)\n"),
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(lambda x, y: 3 * x, "%0 = x\n%1 = Constant(3)\n%2 = Mul(0, 1)\nreturn(%2)\n"),
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(lambda x, y: x * 3, "%0 = x\n%1 = Constant(3)\n%2 = Mul(0, 1)\nreturn(%2)\n"),
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(lambda x, y: x * (-3), "%0 = x\n%1 = Constant(-3)\n%2 = Mul(0, 1)\nreturn(%2)\n"),
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(lambda x, y: x - 11, "%0 = x\n%1 = Constant(11)\n%2 = Sub(0, 1)\nreturn(%2)\n"),
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(lambda x, y: 11 - x, "%0 = Constant(11)\n%1 = x\n%2 = Sub(0, 1)\nreturn(%2)\n"),
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(lambda x, y: (-11) - x, "%0 = Constant(-11)\n%1 = x\n%2 = Sub(0, 1)\nreturn(%2)\n"),
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(
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lambda x, y: x + 13 - y * (-21) * y + 44,
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"%0 = Constant(44)"
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"\n%1 = x"
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"\n%2 = Constant(13)"
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"\n%3 = y"
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"\n%4 = Constant(-21)"
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"\n%5 = Add(1, 2)"
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"\n%6 = Mul(3, 4)"
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"\n%7 = Mul(6, 3)"
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"\n%8 = Sub(5, 7)"
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"\n%9 = Add(8, 0)"
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"\nreturn(%9)\n",
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),
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# Multiple outputs
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(
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lambda x, y: (x + 1, x + y + 2),
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"%0 = x"
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"\n%1 = Constant(1)"
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"\n%2 = Constant(2)"
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"\n%3 = y"
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"\n%4 = Add(0, 1)"
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"\n%5 = Add(0, 3)"
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"\n%6 = Add(5, 2)"
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"\nreturn(%4, %6)\n",
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),
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(
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lambda x, y: (y, x),
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"%0 = y\n%1 = x\nreturn(%0, %1)\n",
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),
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(
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lambda x, y: (x, x + 1),
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"%0 = x\n%1 = Constant(1)\n%2 = Add(0, 1)\nreturn(%0, %2)\n",
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),
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(
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lambda x, y: (x + 1, x + 1),
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"%0 = x"
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"\n%1 = Constant(1)"
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"\n%2 = Constant(1)"
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"\n%3 = Add(0, 1)"
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"\n%4 = Add(0, 2)"
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"\nreturn(%3, %4)\n",
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),
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(
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issue_130_a,
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"%0 = x\n%1 = Constant(1)\n%2 = Add(0, 1)\nreturn(%2, %2)\n",
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),
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(
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issue_130_b,
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"%0 = x\n%1 = Constant(1)\n%2 = Sub(0, 1)\nreturn(%2, %2)\n",
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),
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(
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issue_130_c,
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"%0 = Constant(1)\n%1 = x\n%2 = Sub(0, 1)\nreturn(%2, %2)\n",
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),
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],
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)
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@pytest.mark.parametrize(
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"x_y",
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[
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pytest.param(
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(
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EncryptedScalar(Integer(64, is_signed=False)),
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EncryptedScalar(Integer(64, is_signed=False)),
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),
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id="Encrypted uint",
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),
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pytest.param(
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(
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EncryptedScalar(Integer(64, is_signed=False)),
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ClearScalar(Integer(64, is_signed=False)),
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),
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id="Clear uint",
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),
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],
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)
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def test_print_and_draw_graph(lambda_f, ref_graph_str, x_y):
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"Test get_printable_graph and draw_graph"
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x, y = x_y
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graph = tracing.trace_numpy_function(lambda_f, {"x": x, "y": y})
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draw_graph(graph, show=False)
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str_of_the_graph = get_printable_graph(graph)
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assert str_of_the_graph == ref_graph_str, (
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f"\n==================\nGot \n{str_of_the_graph}"
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f"==================\nExpected \n{ref_graph_str}"
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f"==================\n"
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)
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@pytest.mark.parametrize(
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"lambda_f,params,ref_graph_str",
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[
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(
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lambda x: LOOKUP_TABLE_FROM_2B_TO_4B[x],
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{"x": EncryptedScalar(Integer(2, is_signed=False))},
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"%0 = x\n%1 = TLU(0)\nreturn(%1)\n",
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),
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(
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lambda x: LOOKUP_TABLE_FROM_3B_TO_2B[x + 4],
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{"x": EncryptedScalar(Integer(2, is_signed=False))},
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"%0 = x\n%1 = Constant(4)\n%2 = Add(0, 1)\n%3 = TLU(2)\nreturn(%3)\n",
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),
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],
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)
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def test_print_and_draw_graph_with_direct_tlu(lambda_f, params, ref_graph_str):
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"Test get_printable_graph and draw_graph on graphs with direct table lookup"
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graph = tracing.trace_numpy_function(lambda_f, params)
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draw_graph(graph, show=False)
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str_of_the_graph = get_printable_graph(graph)
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assert str_of_the_graph == ref_graph_str, (
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f"\n==================\nGot \n{str_of_the_graph}"
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f"==================\nExpected \n{ref_graph_str}"
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f"==================\n"
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)
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@pytest.mark.parametrize(
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"lambda_f,params,ref_graph_str",
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[
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# pylint: disable=unnecessary-lambda
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(
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lambda x, y: numpy.dot(x, y),
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{
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"x": EncryptedTensor(Integer(2, is_signed=False), shape=(3,)),
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"y": EncryptedTensor(Integer(2, is_signed=False), shape=(3,)),
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},
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"%0 = x\n%1 = y\n%2 = Dot(0, 1)\nreturn(%2)\n",
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),
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# pylint: enable=unnecessary-lambda
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],
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)
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def test_print_and_draw_graph_with_dot(lambda_f, params, ref_graph_str):
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"Test get_printable_graph and draw_graph on graphs with dot"
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graph = tracing.trace_numpy_function(lambda_f, params)
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draw_graph(graph, show=False)
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str_of_the_graph = get_printable_graph(graph)
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assert str_of_the_graph == ref_graph_str, (
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f"\n==================\nGot \n{str_of_the_graph}"
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f"==================\nExpected \n{ref_graph_str}"
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f"==================\n"
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)
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# Remark that the bitwidths are not particularly correct (eg, a MUL of a 17b times 23b
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# returning 23b), since they are replaced later by the real bitwidths computed on the
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# dataset
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@pytest.mark.parametrize(
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"lambda_f,x_y,ref_graph_str",
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[
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(
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lambda x, y: x + y,
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(
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EncryptedScalar(Integer(64, is_signed=False)),
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EncryptedScalar(Integer(32, is_signed=True)),
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),
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"%0 = x # EncryptedScalar<Integer<unsigned, 64 bits>>"
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"\n%1 = y # EncryptedScalar<Integer<signed, 32 bits>>"
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"\n%2 = Add(0, 1) # EncryptedScalar<Integer<signed, 65 bits>>"
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"\nreturn(%2)\n",
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),
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(
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lambda x, y: x * y,
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(
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EncryptedScalar(Integer(17, is_signed=False)),
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EncryptedScalar(Integer(23, is_signed=False)),
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),
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"%0 = x "
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"# EncryptedScalar<Integer<unsigned, 17 bits>>"
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"\n%1 = y "
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"# EncryptedScalar<Integer<unsigned, 23 bits>>"
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"\n%2 = Mul(0, 1) "
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"# EncryptedScalar<Integer<unsigned, 23 bits>>"
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"\nreturn(%2)\n",
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),
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],
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)
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def test_print_with_show_data_types(lambda_f, x_y, ref_graph_str):
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"""Test get_printable_graph with show_data_types"""
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x, y = x_y
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graph = tracing.trace_numpy_function(lambda_f, {"x": x, "y": y})
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str_of_the_graph = get_printable_graph(graph, show_data_types=True)
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assert str_of_the_graph == ref_graph_str, (
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f"\n==================\nGot \n{str_of_the_graph}"
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f"==================\nExpected \n{ref_graph_str}"
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f"==================\n"
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)
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@pytest.mark.parametrize(
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"lambda_f,params,ref_graph_str",
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[
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(
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lambda x: LOOKUP_TABLE_FROM_2B_TO_4B[x],
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{"x": EncryptedScalar(Integer(2, is_signed=False))},
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"%0 = x "
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"# EncryptedScalar<Integer<unsigned, 2 bits>>"
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"\n%1 = TLU(0) "
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"# EncryptedScalar<Integer<unsigned, 4 bits>>"
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"\nreturn(%1)\n",
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),
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(
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lambda x: LOOKUP_TABLE_FROM_3B_TO_2B[x + 4],
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{"x": EncryptedScalar(Integer(2, is_signed=False))},
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"%0 = x "
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"# EncryptedScalar<Integer<unsigned, 2 bits>>"
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"\n%1 = Constant(4) "
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"# ClearScalar<Integer<unsigned, 3 bits>>"
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"\n%2 = Add(0, 1) "
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"# EncryptedScalar<Integer<unsigned, 3 bits>>"
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"\n%3 = TLU(2) "
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"# EncryptedScalar<Integer<unsigned, 2 bits>>"
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"\nreturn(%3)\n",
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),
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(
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lambda x: LOOKUP_TABLE_FROM_2B_TO_4B[LOOKUP_TABLE_FROM_3B_TO_2B[x + 4]],
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{"x": EncryptedScalar(Integer(2, is_signed=False))},
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"%0 = x "
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"# EncryptedScalar<Integer<unsigned, 2 bits>>"
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"\n%1 = Constant(4) "
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"# ClearScalar<Integer<unsigned, 3 bits>>"
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"\n%2 = Add(0, 1) "
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"# EncryptedScalar<Integer<unsigned, 3 bits>>"
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"\n%3 = TLU(2) "
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"# EncryptedScalar<Integer<unsigned, 2 bits>>"
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"\n%4 = TLU(3) "
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"# EncryptedScalar<Integer<unsigned, 4 bits>>"
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"\nreturn(%4)\n",
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),
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],
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)
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def test_print_with_show_data_types_with_direct_tlu(lambda_f, params, ref_graph_str):
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"""Test get_printable_graph with show_data_types on graphs with direct table lookup"""
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graph = tracing.trace_numpy_function(lambda_f, params)
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draw_graph(graph, show=False)
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str_of_the_graph = get_printable_graph(graph, show_data_types=True)
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assert str_of_the_graph == ref_graph_str, (
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f"\n==================\nGot \n{str_of_the_graph}"
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f"==================\nExpected \n{ref_graph_str}"
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f"==================\n"
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)
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