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[CMSIS-NN] Fixed return data type from pattern callback function#9682

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Merged
manupak merged 2 commits into from
Dec 11, 2021
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[CMSIS-NN] Fixed return data type from pattern callback function #9682

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[CMSIS-NN] Fixed return data type from pattern callback function
Dec 10, 2021
8ed26fc
Fixed lint error
Dec 10, 2021
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4 changes: 2 additions & 2 deletions python/tvm/relay/op/contrib/cmsisnn.py
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Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -135,8 +135,8 @@ def check_qnn_conv2d(pattern):

return (
conv2d.attrs.out_dtype == "int32"
and conv2d.attrs.padding[2] == 0
and conv2d.attrs.padding[3] == 0
and int(conv2d.attrs.padding[2]) == 0

@manupakmanupakDec 10, 2021

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I believe this is the actual fix. Am I right ? (because others are changes to test code).
What test would fail in this PR without this change ?

I think we could have a simpler test to check whether graph partitioning works with conv2d with padding values for top, left, bottom and right.

and int(conv2d.attrs.padding[3]) == 0
and conv2d_input.checked_type.dtype == "int8"
and conv2d_weight.checked_type.dtype == "int8"
and pattern.checked_type.dtype == "int8"
Expand Down
15 changes: 11 additions & 4 deletions tests/python/contrib/test_cmsisnn/test_conv2d.py
View file
Open in desktop
Original file line numberDiff line numberDiff line change
Expand Up@@ -69,6 +69,8 @@ def make_model(
kernel_w = kernel_shape[w_index]
invar = relay.var("input", shape=shape, dtype=dtype)
p = (0, 0, 0, 0)
if padding == "INVALID":
p = [1, 2, 1, 2]
if padding == "SAME":
p = get_same_padding((shape[1], shape[2]), (kernel_h, kernel_w), dilation, strides)
invar = relay.nn.pad(
Expand DownExpand Up@@ -351,15 +353,19 @@ def parameterize_for_invalid_model(test):
in_dtype = ["uint8", "int8"]
kernel_dtype = ["uint8", "int8"]
kernel_zero_point = [-33, 10, 0]
all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point)
padding = ["SAME", "INVALID"]
all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point, padding)
all_combinations = filter(
lambda parameters: not (
parameters[0] == "int8" and parameters[1] == "int8" and parameters[2] == 0
parameters[0] == "int8"
and parameters[1] == "int8"
and parameters[2] == 0
and parameters[3] == "SAME"
),
all_combinations,
)
return pytest.mark.parametrize(
["in_dtype", "kernel_dtype", "kernel_zero_point"],
["in_dtype", "kernel_dtype", "kernel_zero_point", "padding"],
all_combinations,
)(test)

Expand All@@ -370,6 +376,7 @@ def test_invalid_parameters(
in_dtype,
kernel_dtype,
kernel_zero_point,
padding,
):
ifm_shape = (1, 28, 28, 12)
out_channels = 2
Expand DownExpand Up@@ -400,7 +407,7 @@ def test_invalid_parameters(
kernel_scale=kernel_scale,
output_zero_point=output_zero_point,
output_scale=output_scale,
padding="SAME",
padding=padding,
strides=(1, 1),
dilation=(1, 1),
groups=1,
Expand Down
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[CMSIS-NN] Fixed return data type from pattern callback function by asparkhi · Pull Request #9682 · apache/tvm · GitHub
Skip to content
[CMSIS-NN] Fixed return data type from pattern callback function#9682

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 Merged

manupak
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Dec 11, 2021
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[CMSIS-NN] Fixed return data type from pattern callback function
#9682
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0541a0c

[CMSIS-NN] Fixed return data type from pattern callback function

Dec 10, 2021
8ed26fc

Fixed lint error

Dec 10, 2021

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4 changes: 2 additions & 2 deletions
python/tvm/relay/op/contrib/cmsisnn.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -135,8 +135,8 @@ def check_qnn_conv2d(pattern):

 return (
 conv2d.attrs.out_dtype == "int32"
 and conv2d.attrs.padding[2] == 0
 and conv2d.attrs.padding[3] == 0
 and int(conv2d.attrs.padding[2]) == 0
@manupakmanupakDec 10, 2021

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I believe this is the actual fix. Am I right ? (because others are changes to test code).

What test would fail in this PR without this change ?
I think we could have a simpler test to check whether graph partitioning works with conv2d with padding values for top, left, bottom and right.
 and int(conv2d.attrs.padding[3]) == 0
 and conv2d_input.checked_type.dtype == "int8"
 and conv2d_weight.checked_type.dtype == "int8"
 and pattern.checked_type.dtype == "int8"
Expand Down

15 changes: 11 additions & 4 deletions
tests/python/contrib/test_cmsisnn/test_conv2d.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -69,6 +69,8 @@ def make_model(
 kernel_w = kernel_shape[w_index]
 invar = relay.var("input", shape=shape, dtype=dtype)
 p = (0, 0, 0, 0)
 if padding == "INVALID":
 p = [1, 2, 1, 2]
 if padding == "SAME":
 p = get_same_padding((shape[1], shape[2]), (kernel_h, kernel_w), dilation, strides)
 invar = relay.nn.pad(
Expand DownExpand Up@@ -351,15 +353,19 @@ def parameterize_for_invalid_model(test):
 in_dtype = ["uint8", "int8"]
 kernel_dtype = ["uint8", "int8"]
 kernel_zero_point = [-33, 10, 0]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point)
 padding = ["SAME", "INVALID"]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point, padding)
 all_combinations = filter(
 lambda parameters: not (
 parameters[0] == "int8" and parameters[1] == "int8" and parameters[2] == 0
 parameters[0] == "int8"
 and parameters[1] == "int8"
 and parameters[2] == 0
 and parameters[3] == "SAME"
 ),
 all_combinations,
 )
 return pytest.mark.parametrize(
 ["in_dtype", "kernel_dtype", "kernel_zero_point"],
 ["in_dtype", "kernel_dtype", "kernel_zero_point", "padding"],
 all_combinations,
 )(test)

Expand All@@ -370,6 +376,7 @@ def test_invalid_parameters(
 in_dtype,
 kernel_dtype,
 kernel_zero_point,
 padding,
):
 ifm_shape = (1, 28, 28, 12)
 out_channels = 2
Expand DownExpand Up@@ -400,7 +407,7 @@ def test_invalid_parameters(
 kernel_scale=kernel_scale,
 output_zero_point=output_zero_point,
 output_scale=output_scale,
 padding="SAME",
 padding=padding,
 strides=(1, 1),
 dilation=(1, 1),
 groups=1,
Expand Down

, 'i');
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var style = document.createElement('style');
style.textContent = '
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[CMSIS-NN] Fixed return data type from pattern callback function by asparkhi · Pull Request #9682 · apache/tvm · GitHub
Skip to content
[CMSIS-NN] Fixed return data type from pattern callback function#9682

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 Merged

manupak
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Dec 11, 2021
 Merged


[CMSIS-NN] Fixed return data type from pattern callback function
#9682
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0541a0c

[CMSIS-NN] Fixed return data type from pattern callback function

Dec 10, 2021
8ed26fc

Fixed lint error

Dec 10, 2021

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4 changes: 2 additions & 2 deletions
python/tvm/relay/op/contrib/cmsisnn.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -135,8 +135,8 @@ def check_qnn_conv2d(pattern):

 return (
 conv2d.attrs.out_dtype == "int32"
 and conv2d.attrs.padding[2] == 0
 and conv2d.attrs.padding[3] == 0
 and int(conv2d.attrs.padding[2]) == 0
@manupakmanupakDec 10, 2021

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I believe this is the actual fix. Am I right ? (because others are changes to test code).

What test would fail in this PR without this change ?
I think we could have a simpler test to check whether graph partitioning works with conv2d with padding values for top, left, bottom and right.
 and int(conv2d.attrs.padding[3]) == 0
 and conv2d_input.checked_type.dtype == "int8"
 and conv2d_weight.checked_type.dtype == "int8"
 and pattern.checked_type.dtype == "int8"
Expand Down

15 changes: 11 additions & 4 deletions
tests/python/contrib/test_cmsisnn/test_conv2d.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -69,6 +69,8 @@ def make_model(
 kernel_w = kernel_shape[w_index]
 invar = relay.var("input", shape=shape, dtype=dtype)
 p = (0, 0, 0, 0)
 if padding == "INVALID":
 p = [1, 2, 1, 2]
 if padding == "SAME":
 p = get_same_padding((shape[1], shape[2]), (kernel_h, kernel_w), dilation, strides)
 invar = relay.nn.pad(
Expand DownExpand Up@@ -351,15 +353,19 @@ def parameterize_for_invalid_model(test):
 in_dtype = ["uint8", "int8"]
 kernel_dtype = ["uint8", "int8"]
 kernel_zero_point = [-33, 10, 0]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point)
 padding = ["SAME", "INVALID"]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point, padding)
 all_combinations = filter(
 lambda parameters: not (
 parameters[0] == "int8" and parameters[1] == "int8" and parameters[2] == 0
 parameters[0] == "int8"
 and parameters[1] == "int8"
 and parameters[2] == 0
 and parameters[3] == "SAME"
 ),
 all_combinations,
 )
 return pytest.mark.parametrize(
 ["in_dtype", "kernel_dtype", "kernel_zero_point"],
 ["in_dtype", "kernel_dtype", "kernel_zero_point", "padding"],
 all_combinations,
 )(test)

Expand All@@ -370,6 +376,7 @@ def test_invalid_parameters(
 in_dtype,
 kernel_dtype,
 kernel_zero_point,
 padding,
):
 ifm_shape = (1, 28, 28, 12)
 out_channels = 2
Expand DownExpand Up@@ -400,7 +407,7 @@ def test_invalid_parameters(
 kernel_scale=kernel_scale,
 output_zero_point=output_zero_point,
 output_scale=output_scale,
 padding="SAME",
 padding=padding,
 strides=(1, 1),
 dilation=(1, 1),
 groups=1,
Expand Down

, 'i');
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// Highlight search terms from Google/DuckDuckGo/Bing referrer
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var ref = document.referrer;
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[CMSIS-NN] Fixed return data type from pattern callback function by asparkhi · Pull Request #9682 · apache/tvm · GitHub
Skip to content
[CMSIS-NN] Fixed return data type from pattern callback function#9682

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 Merged

manupak
merged 2 commits into

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Dec 11, 2021
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[CMSIS-NN] Fixed return data type from pattern callback function
#9682
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0541a0c

[CMSIS-NN] Fixed return data type from pattern callback function

Dec 10, 2021
8ed26fc

Fixed lint error

Dec 10, 2021

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4 changes: 2 additions & 2 deletions
python/tvm/relay/op/contrib/cmsisnn.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -135,8 +135,8 @@ def check_qnn_conv2d(pattern):

 return (
 conv2d.attrs.out_dtype == "int32"
 and conv2d.attrs.padding[2] == 0
 and conv2d.attrs.padding[3] == 0
 and int(conv2d.attrs.padding[2]) == 0
@manupakmanupakDec 10, 2021

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I believe this is the actual fix. Am I right ? (because others are changes to test code).

What test would fail in this PR without this change ?
I think we could have a simpler test to check whether graph partitioning works with conv2d with padding values for top, left, bottom and right.
 and int(conv2d.attrs.padding[3]) == 0
 and conv2d_input.checked_type.dtype == "int8"
 and conv2d_weight.checked_type.dtype == "int8"
 and pattern.checked_type.dtype == "int8"
Expand Down

15 changes: 11 additions & 4 deletions
tests/python/contrib/test_cmsisnn/test_conv2d.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -69,6 +69,8 @@ def make_model(
 kernel_w = kernel_shape[w_index]
 invar = relay.var("input", shape=shape, dtype=dtype)
 p = (0, 0, 0, 0)
 if padding == "INVALID":
 p = [1, 2, 1, 2]
 if padding == "SAME":
 p = get_same_padding((shape[1], shape[2]), (kernel_h, kernel_w), dilation, strides)
 invar = relay.nn.pad(
Expand DownExpand Up@@ -351,15 +353,19 @@ def parameterize_for_invalid_model(test):
 in_dtype = ["uint8", "int8"]
 kernel_dtype = ["uint8", "int8"]
 kernel_zero_point = [-33, 10, 0]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point)
 padding = ["SAME", "INVALID"]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point, padding)
 all_combinations = filter(
 lambda parameters: not (
 parameters[0] == "int8" and parameters[1] == "int8" and parameters[2] == 0
 parameters[0] == "int8"
 and parameters[1] == "int8"
 and parameters[2] == 0
 and parameters[3] == "SAME"
 ),
 all_combinations,
 )
 return pytest.mark.parametrize(
 ["in_dtype", "kernel_dtype", "kernel_zero_point"],
 ["in_dtype", "kernel_dtype", "kernel_zero_point", "padding"],
 all_combinations,
 )(test)

Expand All@@ -370,6 +376,7 @@ def test_invalid_parameters(
 in_dtype,
 kernel_dtype,
 kernel_zero_point,
 padding,
):
 ifm_shape = (1, 28, 28, 12)
 out_channels = 2
Expand DownExpand Up@@ -400,7 +407,7 @@ def test_invalid_parameters(
 kernel_scale=kernel_scale,
 output_zero_point=output_zero_point,
 output_scale=output_scale,
 padding="SAME",
 padding=padding,
 strides=(1, 1),
 dilation=(1, 1),
 groups=1,
Expand Down

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'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',
'ref', 'ref_src', 'source', 'medium', 'campaign'];
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try {
var u = new URL(url, window.location.origin);
var changed = false;
trackingParams.forEach(function(p) {
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[CMSIS-NN] Fixed return data type from pattern callback function by asparkhi · Pull Request #9682 · apache/tvm · GitHub
Skip to content
[CMSIS-NN] Fixed return data type from pattern callback function#9682

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 Merged

manupak
merged 2 commits into

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Dec 11, 2021
 Merged


[CMSIS-NN] Fixed return data type from pattern callback function
#9682
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0541a0c

[CMSIS-NN] Fixed return data type from pattern callback function

Dec 10, 2021
8ed26fc

Fixed lint error

Dec 10, 2021

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4 changes: 2 additions & 2 deletions
python/tvm/relay/op/contrib/cmsisnn.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -135,8 +135,8 @@ def check_qnn_conv2d(pattern):

 return (
 conv2d.attrs.out_dtype == "int32"
 and conv2d.attrs.padding[2] == 0
 and conv2d.attrs.padding[3] == 0
 and int(conv2d.attrs.padding[2]) == 0
@manupakmanupakDec 10, 2021

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I believe this is the actual fix. Am I right ? (because others are changes to test code).

What test would fail in this PR without this change ?
I think we could have a simpler test to check whether graph partitioning works with conv2d with padding values for top, left, bottom and right.
 and int(conv2d.attrs.padding[3]) == 0
 and conv2d_input.checked_type.dtype == "int8"
 and conv2d_weight.checked_type.dtype == "int8"
 and pattern.checked_type.dtype == "int8"
Expand Down

15 changes: 11 additions & 4 deletions
tests/python/contrib/test_cmsisnn/test_conv2d.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -69,6 +69,8 @@ def make_model(
 kernel_w = kernel_shape[w_index]
 invar = relay.var("input", shape=shape, dtype=dtype)
 p = (0, 0, 0, 0)
 if padding == "INVALID":
 p = [1, 2, 1, 2]
 if padding == "SAME":
 p = get_same_padding((shape[1], shape[2]), (kernel_h, kernel_w), dilation, strides)
 invar = relay.nn.pad(
Expand DownExpand Up@@ -351,15 +353,19 @@ def parameterize_for_invalid_model(test):
 in_dtype = ["uint8", "int8"]
 kernel_dtype = ["uint8", "int8"]
 kernel_zero_point = [-33, 10, 0]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point)
 padding = ["SAME", "INVALID"]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point, padding)
 all_combinations = filter(
 lambda parameters: not (
 parameters[0] == "int8" and parameters[1] == "int8" and parameters[2] == 0
 parameters[0] == "int8"
 and parameters[1] == "int8"
 and parameters[2] == 0
 and parameters[3] == "SAME"
 ),
 all_combinations,
 )
 return pytest.mark.parametrize(
 ["in_dtype", "kernel_dtype", "kernel_zero_point"],
 ["in_dtype", "kernel_dtype", "kernel_zero_point", "padding"],
 all_combinations,
 )(test)

Expand All@@ -370,6 +376,7 @@ def test_invalid_parameters(
 in_dtype,
 kernel_dtype,
 kernel_zero_point,
 padding,
):
 ifm_shape = (1, 28, 28, 12)
 out_channels = 2
Expand DownExpand Up@@ -400,7 +407,7 @@ def test_invalid_parameters(
 kernel_scale=kernel_scale,
 output_zero_point=output_zero_point,
 output_scale=output_scale,
 padding="SAME",
 padding=padding,
 strides=(1, 1),
 dilation=(1, 1),
 groups=1,
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Auto-enable theater mode on YouTube
(function() {
function tryTheater() {
var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]');
if (btn && !btn.classList.contains('activated')) {
btn.click();
}
}
// Try immediately
tryTheater();
// Try after navigation (SPA)
var lastUrl = location.href;
setInterval(function() {
if (location.href !== lastUrl) {
lastUrl = location.href;
setTimeout(tryTheater, 500);
}
}, 1000);
// Also try on player load
var observer = new MutationObserver(tryTheater);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '
[CMSIS-NN] Fixed return data type from pattern callback function by asparkhi · Pull Request #9682 · apache/tvm · GitHub
Skip to content
[CMSIS-NN] Fixed return data type from pattern callback function#9682

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 Merged

manupak
merged 2 commits into

from

Dec 11, 2021
 Merged


[CMSIS-NN] Fixed return data type from pattern callback function
#9682
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0541a0c

[CMSIS-NN] Fixed return data type from pattern callback function

Dec 10, 2021
8ed26fc

Fixed lint error

Dec 10, 2021

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4 changes: 2 additions & 2 deletions
python/tvm/relay/op/contrib/cmsisnn.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -135,8 +135,8 @@ def check_qnn_conv2d(pattern):

 return (
 conv2d.attrs.out_dtype == "int32"
 and conv2d.attrs.padding[2] == 0
 and conv2d.attrs.padding[3] == 0
 and int(conv2d.attrs.padding[2]) == 0
@manupakmanupakDec 10, 2021

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I believe this is the actual fix. Am I right ? (because others are changes to test code).

What test would fail in this PR without this change ?
I think we could have a simpler test to check whether graph partitioning works with conv2d with padding values for top, left, bottom and right.
 and int(conv2d.attrs.padding[3]) == 0
 and conv2d_input.checked_type.dtype == "int8"
 and conv2d_weight.checked_type.dtype == "int8"
 and pattern.checked_type.dtype == "int8"
Expand Down

15 changes: 11 additions & 4 deletions
tests/python/contrib/test_cmsisnn/test_conv2d.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -69,6 +69,8 @@ def make_model(
 kernel_w = kernel_shape[w_index]
 invar = relay.var("input", shape=shape, dtype=dtype)
 p = (0, 0, 0, 0)
 if padding == "INVALID":
 p = [1, 2, 1, 2]
 if padding == "SAME":
 p = get_same_padding((shape[1], shape[2]), (kernel_h, kernel_w), dilation, strides)
 invar = relay.nn.pad(
Expand DownExpand Up@@ -351,15 +353,19 @@ def parameterize_for_invalid_model(test):
 in_dtype = ["uint8", "int8"]
 kernel_dtype = ["uint8", "int8"]
 kernel_zero_point = [-33, 10, 0]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point)
 padding = ["SAME", "INVALID"]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point, padding)
 all_combinations = filter(
 lambda parameters: not (
 parameters[0] == "int8" and parameters[1] == "int8" and parameters[2] == 0
 parameters[0] == "int8"
 and parameters[1] == "int8"
 and parameters[2] == 0
 and parameters[3] == "SAME"
 ),
 all_combinations,
 )
 return pytest.mark.parametrize(
 ["in_dtype", "kernel_dtype", "kernel_zero_point"],
 ["in_dtype", "kernel_dtype", "kernel_zero_point", "padding"],
 all_combinations,
 )(test)

Expand All@@ -370,6 +376,7 @@ def test_invalid_parameters(
 in_dtype,
 kernel_dtype,
 kernel_zero_point,
 padding,
):
 ifm_shape = (1, 28, 28, 12)
 out_channels = 2
Expand DownExpand Up@@ -400,7 +407,7 @@ def test_invalid_parameters(
 kernel_scale=kernel_scale,
 output_zero_point=output_zero_point,
 output_scale=output_scale,
 padding="SAME",
 padding=padding,
 strides=(1, 1),
 dilation=(1, 1),
 groups=1,
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
// Remove or un-stick sticky/fixed headers that block content
(function() {
function unstick() {
document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) {
if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {
el.style.position = 'static';
el.style.top = 'auto';
el.style.zIndex = 'auto';
}
});
}
unstick();
var observer = new MutationObserver(unstick);
observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });
})();
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
})();
[CMSIS-NN] Fixed return data type from pattern callback function by asparkhi · Pull Request #9682 · apache/tvm · GitHub
Skip to content
[CMSIS-NN] Fixed return data type from pattern callback function#9682

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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to your account

 Merged

manupak
merged 2 commits into

from

Dec 11, 2021
 Merged


[CMSIS-NN] Fixed return data type from pattern callback function
#9682
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0541a0c

[CMSIS-NN] Fixed return data type from pattern callback function

Dec 10, 2021
8ed26fc

Fixed lint error

Dec 10, 2021

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4 changes: 2 additions & 2 deletions
python/tvm/relay/op/contrib/cmsisnn.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -135,8 +135,8 @@ def check_qnn_conv2d(pattern):

 return (
 conv2d.attrs.out_dtype == "int32"
 and conv2d.attrs.padding[2] == 0
 and conv2d.attrs.padding[3] == 0
 and int(conv2d.attrs.padding[2]) == 0
@manupakmanupakDec 10, 2021

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Contributor
Choose a reason for hiding this comment

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I believe this is the actual fix. Am I right ? (because others are changes to test code).

What test would fail in this PR without this change ?
I think we could have a simpler test to check whether graph partitioning works with conv2d with padding values for top, left, bottom and right.
 and int(conv2d.attrs.padding[3]) == 0
 and conv2d_input.checked_type.dtype == "int8"
 and conv2d_weight.checked_type.dtype == "int8"
 and pattern.checked_type.dtype == "int8"
Expand Down

15 changes: 11 additions & 4 deletions
tests/python/contrib/test_cmsisnn/test_conv2d.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -69,6 +69,8 @@ def make_model(
 kernel_w = kernel_shape[w_index]
 invar = relay.var("input", shape=shape, dtype=dtype)
 p = (0, 0, 0, 0)
 if padding == "INVALID":
 p = [1, 2, 1, 2]
 if padding == "SAME":
 p = get_same_padding((shape[1], shape[2]), (kernel_h, kernel_w), dilation, strides)
 invar = relay.nn.pad(
Expand DownExpand Up@@ -351,15 +353,19 @@ def parameterize_for_invalid_model(test):
 in_dtype = ["uint8", "int8"]
 kernel_dtype = ["uint8", "int8"]
 kernel_zero_point = [-33, 10, 0]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point)
 padding = ["SAME", "INVALID"]
 all_combinations = itertools.product(in_dtype, kernel_dtype, kernel_zero_point, padding)
 all_combinations = filter(
 lambda parameters: not (
 parameters[0] == "int8" and parameters[1] == "int8" and parameters[2] == 0
 parameters[0] == "int8"
 and parameters[1] == "int8"
 and parameters[2] == 0
 and parameters[3] == "SAME"
 ),
 all_combinations,
 )
 return pytest.mark.parametrize(
 ["in_dtype", "kernel_dtype", "kernel_zero_point"],
 ["in_dtype", "kernel_dtype", "kernel_zero_point", "padding"],
 all_combinations,
 )(test)

Expand All@@ -370,6 +376,7 @@ def test_invalid_parameters(
 in_dtype,
 kernel_dtype,
 kernel_zero_point,
 padding,
):
 ifm_shape = (1, 28, 28, 12)
 out_channels = 2
Expand DownExpand Up@@ -400,7 +407,7 @@ def test_invalid_parameters(
 kernel_scale=kernel_scale,
 output_zero_point=output_zero_point,
 output_scale=output_scale,
 padding="SAME",
 padding=padding,
 strides=(1, 1),
 dilation=(1, 1),
 groups=1,
Expand Down