Merged all support functions into read_graph; returning atoms - #4

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Merged all support functions into read_graph; returning atoms#4
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@anshuman23anshuman23 commented May 17, 2018

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@josevalim as discussed in #3 , merged all graph reading capabilities into the read_graph function. This function returns a TF_Graph on successful loading of graph and an {:error,"Unable to load graph"} tuple on an unsuccessful attempt.

Example is as follows (classify_image_graph_def.pb is from Google's Imagenet model):

iex(1)>graph=Tensorflex.read_graph("classify_image_graph_def.pb")2018-05-1723:36:16.488469: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supportsinstructionsthatthisTensorFlowbinarywasnotcompiledtouse: SSE4.1 SSE4.2 AVX AVX2 FMA 2018-05-1723:36:16.774442: W tensorflow/core/framework/op_def_util.cc:334] OpBatchNormWithGlobalNormalization isdeprecated.It will cease to work inGraphDefversion9.Use tf.nn.batch_normalization().Successfullyimportedgraph#Reference<0.1610607974.1988231169.250293>iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,'Unable to import graph'}

I have an idea for the "story" around the graph loading we had talked about, so I'll be merging this PR as already discussed and adding the details of that in the next PR for your review.

@anshuman23
anshuman23 merged commit ef4efe3 into masterMay 17, 2018
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I love the return types. Great job!

Note though that you are returning a charlist (single-quoted) in the error message while a string/binary (double-quoted) would be preferred:

iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,"Unable to import graph"}

josevalim
josevalim reviewed May 18, 2018
View reviewed changes
Comment threadc_src/Tensorflex.c
if (TF_GetCode(status) != TF_OK) {
fprintf(stderr, "ERROR: Unable to import graph %s", TF_Message(status));
return 1;
return enif_make_tuple2(env,enif_make_atom(env,"error"),enif_make_string(env, "Unable to import graph", ERL_NIF_LATIN1));

@josevalimjosevalimMay 18, 2018•
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Just to clarify, an Erlang string is not the same as an Elixir string. So we need to use the binary API here.

Also, note that we can return a better error, so let's do that. Here are all of the possible error values from Tensorflow. The idea is to convert each of them into an atom. So if we get TF_NOT_FOUND, we should return {:error, :not_found}. This will probably be very common, so we can encapsulate it in a C procedure.

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Noted. I completely agree-- I didn't realize I was returning char lists. Now I've shifted to enif_make_binary() wherever required. Also added this and the TF error codes to the latest PR.

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Merged all support functions into read_graph; returning atoms - #4
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anshuman23 merged 1 commit into
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May 17, 2018
Merged
Merged all support functions into read_graph; returning atoms#4
anshuman23 merged 1 commit into
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@anshuman23
@anshuman23anshuman23
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May 17, 2018

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@josevalim as discussed in #3 , merged all graph reading capabilities into the read_graph function. This function returns a TF_Graph on successful loading of graph and an {:error,"Unable to load graph"} tuple on an unsuccessful attempt.
Example is as follows (classify_image_graph_def.pb is from Google's Imagenet model):
iex(1)>graph=Tensorflex.read_graph("classify_image_graph_def.pb")2018-05-1723:36:16.488469: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supportsinstructionsthatthisTensorFlowbinarywasnotcompiledtouse: SSE4.1 SSE4.2 AVX AVX2 FMA 2018-05-1723:36:16.774442: W tensorflow/core/framework/op_def_util.cc:334] OpBatchNormWithGlobalNormalization isdeprecated.It will cease to work inGraphDefversion9.Use tf.nn.batch_normalization().Successfullyimportedgraph#Reference<0.1610607974.1988231169.250293>iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,'Unable to import graph'}
I have an idea for the "story" around the graph loading we had talked about, so I'll be merging this PR as already discussed and adding the details of that in the next PR for your review.
@anshuman23
anshuman23
merged commit ef4efe3
into
masterMay 17, 2018
@josevalim
josevalim
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May 18, 2018

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I love the return types. Great job!
Note though that you are returning a charlist (single-quoted) in the error message while a string/binary (double-quoted) would be preferred:
iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,"Unable to import graph"}
josevalim
josevalim
reviewed
May 18, 2018
View reviewed changes
Comment threadc_src/Tensorflex.c
 if (TF_GetCode(status) != TF_OK) {
 fprintf(stderr, "ERROR: Unable to import graph %s", TF_Message(status));
 return 1;
 return enif_make_tuple2(env,enif_make_atom(env,"error"),enif_make_string(env, "Unable to import graph", ERL_NIF_LATIN1));
@josevalimjosevalimMay 18, 2018•

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Just to clarify, an Erlang string is not the same as an Elixir string. So we need to use the binary API here.
Also, note that we can return a better error, so let's do that. Here are all of the possible error values from Tensorflow. The idea is to convert each of them into an atom. So if we get TF_NOT_FOUND, we should return {:error, :not_found}. This will probably be very common, so we can encapsulate it in a C procedure.
@anshuman23anshuman23May 18, 2018

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Noted. I completely agree-- I didn't realize I was returning char lists. Now I've shifted to enif_make_binary() wherever required. Also added this and the TF error codes to the latest PR.
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
Merged all support functions into read_graph; returning atoms - #4
Merged
anshuman23 merged 1 commit into
masterfrom 
dev
May 17, 2018
Merged
Merged all support functions into read_graph; returning atoms#4
anshuman23 merged 1 commit into
masterfrom 
dev
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@anshuman23
@anshuman23anshuman23
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May 17, 2018

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@josevalim as discussed in #3 , merged all graph reading capabilities into the read_graph function. This function returns a TF_Graph on successful loading of graph and an {:error,"Unable to load graph"} tuple on an unsuccessful attempt.
Example is as follows (classify_image_graph_def.pb is from Google's Imagenet model):
iex(1)>graph=Tensorflex.read_graph("classify_image_graph_def.pb")2018-05-1723:36:16.488469: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supportsinstructionsthatthisTensorFlowbinarywasnotcompiledtouse: SSE4.1 SSE4.2 AVX AVX2 FMA 2018-05-1723:36:16.774442: W tensorflow/core/framework/op_def_util.cc:334] OpBatchNormWithGlobalNormalization isdeprecated.It will cease to work inGraphDefversion9.Use tf.nn.batch_normalization().Successfullyimportedgraph#Reference<0.1610607974.1988231169.250293>iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,'Unable to import graph'}
I have an idea for the "story" around the graph loading we had talked about, so I'll be merging this PR as already discussed and adding the details of that in the next PR for your review.
@anshuman23
anshuman23
merged commit ef4efe3
into
masterMay 17, 2018
@josevalim
josevalim
commented
May 18, 2018

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I love the return types. Great job!
Note though that you are returning a charlist (single-quoted) in the error message while a string/binary (double-quoted) would be preferred:
iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,"Unable to import graph"}
josevalim
josevalim
reviewed
May 18, 2018
View reviewed changes
Comment threadc_src/Tensorflex.c
 if (TF_GetCode(status) != TF_OK) {
 fprintf(stderr, "ERROR: Unable to import graph %s", TF_Message(status));
 return 1;
 return enif_make_tuple2(env,enif_make_atom(env,"error"),enif_make_string(env, "Unable to import graph", ERL_NIF_LATIN1));
@josevalimjosevalimMay 18, 2018•

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Just to clarify, an Erlang string is not the same as an Elixir string. So we need to use the binary API here.
Also, note that we can return a better error, so let's do that. Here are all of the possible error values from Tensorflow. The idea is to convert each of them into an atom. So if we get TF_NOT_FOUND, we should return {:error, :not_found}. This will probably be very common, so we can encapsulate it in a C procedure.
@anshuman23anshuman23May 18, 2018

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Noted. I completely agree-- I didn't realize I was returning char lists. Now I've shifted to enif_make_binary() wherever required. Also added this and the TF error codes to the latest PR.
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Merged all support functions into read_graph; returning atoms - #4
Merged
anshuman23 merged 1 commit into
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dev
May 17, 2018
Merged
Merged all support functions into read_graph; returning atoms#4
anshuman23 merged 1 commit into
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@anshuman23
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@josevalim as discussed in #3 , merged all graph reading capabilities into the read_graph function. This function returns a TF_Graph on successful loading of graph and an {:error,"Unable to load graph"} tuple on an unsuccessful attempt.
Example is as follows (classify_image_graph_def.pb is from Google's Imagenet model):
iex(1)>graph=Tensorflex.read_graph("classify_image_graph_def.pb")2018-05-1723:36:16.488469: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supportsinstructionsthatthisTensorFlowbinarywasnotcompiledtouse: SSE4.1 SSE4.2 AVX AVX2 FMA 2018-05-1723:36:16.774442: W tensorflow/core/framework/op_def_util.cc:334] OpBatchNormWithGlobalNormalization isdeprecated.It will cease to work inGraphDefversion9.Use tf.nn.batch_normalization().Successfullyimportedgraph#Reference<0.1610607974.1988231169.250293>iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,'Unable to import graph'}
I have an idea for the "story" around the graph loading we had talked about, so I'll be merging this PR as already discussed and adding the details of that in the next PR for your review.
@anshuman23
anshuman23
merged commit ef4efe3
into
masterMay 17, 2018
@josevalim
josevalim
commented
May 18, 2018

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I love the return types. Great job!
Note though that you are returning a charlist (single-quoted) in the error message while a string/binary (double-quoted) would be preferred:
iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,"Unable to import graph"}
josevalim
josevalim
reviewed
May 18, 2018
View reviewed changes
Comment threadc_src/Tensorflex.c
 if (TF_GetCode(status) != TF_OK) {
 fprintf(stderr, "ERROR: Unable to import graph %s", TF_Message(status));
 return 1;
 return enif_make_tuple2(env,enif_make_atom(env,"error"),enif_make_string(env, "Unable to import graph", ERL_NIF_LATIN1));
@josevalimjosevalimMay 18, 2018•

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Just to clarify, an Erlang string is not the same as an Elixir string. So we need to use the binary API here.
Also, note that we can return a better error, so let's do that. Here are all of the possible error values from Tensorflow. The idea is to convert each of them into an atom. So if we get TF_NOT_FOUND, we should return {:error, :not_found}. This will probably be very common, so we can encapsulate it in a C procedure.
@anshuman23anshuman23May 18, 2018

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Noted. I completely agree-- I didn't realize I was returning char lists. Now I've shifted to enif_make_binary() wherever required. Also added this and the TF error codes to the latest PR.
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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Merged all support functions into read_graph; returning atoms - #4
Merged
anshuman23 merged 1 commit into
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May 17, 2018
Merged
Merged all support functions into read_graph; returning atoms#4
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dev
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@anshuman23
@anshuman23anshuman23
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@josevalim as discussed in #3 , merged all graph reading capabilities into the read_graph function. This function returns a TF_Graph on successful loading of graph and an {:error,"Unable to load graph"} tuple on an unsuccessful attempt.
Example is as follows (classify_image_graph_def.pb is from Google's Imagenet model):
iex(1)>graph=Tensorflex.read_graph("classify_image_graph_def.pb")2018-05-1723:36:16.488469: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supportsinstructionsthatthisTensorFlowbinarywasnotcompiledtouse: SSE4.1 SSE4.2 AVX AVX2 FMA 2018-05-1723:36:16.774442: W tensorflow/core/framework/op_def_util.cc:334] OpBatchNormWithGlobalNormalization isdeprecated.It will cease to work inGraphDefversion9.Use tf.nn.batch_normalization().Successfullyimportedgraph#Reference<0.1610607974.1988231169.250293>iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,'Unable to import graph'}
I have an idea for the "story" around the graph loading we had talked about, so I'll be merging this PR as already discussed and adding the details of that in the next PR for your review.
@anshuman23
anshuman23
merged commit ef4efe3
into
masterMay 17, 2018
@josevalim
josevalim
commented
May 18, 2018

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I love the return types. Great job!
Note though that you are returning a charlist (single-quoted) in the error message while a string/binary (double-quoted) would be preferred:
iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,"Unable to import graph"}
josevalim
josevalim
reviewed
May 18, 2018
View reviewed changes
Comment threadc_src/Tensorflex.c
 if (TF_GetCode(status) != TF_OK) {
 fprintf(stderr, "ERROR: Unable to import graph %s", TF_Message(status));
 return 1;
 return enif_make_tuple2(env,enif_make_atom(env,"error"),enif_make_string(env, "Unable to import graph", ERL_NIF_LATIN1));
@josevalimjosevalimMay 18, 2018•

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Just to clarify, an Erlang string is not the same as an Elixir string. So we need to use the binary API here.
Also, note that we can return a better error, so let's do that. Here are all of the possible error values from Tensorflow. The idea is to convert each of them into an atom. So if we get TF_NOT_FOUND, we should return {:error, :not_found}. This will probably be very common, so we can encapsulate it in a C procedure.
@anshuman23anshuman23May 18, 2018

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Noted. I completely agree-- I didn't realize I was returning char lists. Now I've shifted to enif_make_binary() wherever required. Also added this and the TF error codes to the latest PR.
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Merged all support functions into read_graph; returning atoms - #4
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Merged
Merged all support functions into read_graph; returning atoms#4
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@josevalim as discussed in #3 , merged all graph reading capabilities into the read_graph function. This function returns a TF_Graph on successful loading of graph and an {:error,"Unable to load graph"} tuple on an unsuccessful attempt.
Example is as follows (classify_image_graph_def.pb is from Google's Imagenet model):
iex(1)>graph=Tensorflex.read_graph("classify_image_graph_def.pb")2018-05-1723:36:16.488469: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supportsinstructionsthatthisTensorFlowbinarywasnotcompiledtouse: SSE4.1 SSE4.2 AVX AVX2 FMA 2018-05-1723:36:16.774442: W tensorflow/core/framework/op_def_util.cc:334] OpBatchNormWithGlobalNormalization isdeprecated.It will cease to work inGraphDefversion9.Use tf.nn.batch_normalization().Successfullyimportedgraph#Reference<0.1610607974.1988231169.250293>iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,'Unable to import graph'}
I have an idea for the "story" around the graph loading we had talked about, so I'll be merging this PR as already discussed and adding the details of that in the next PR for your review.
@anshuman23
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merged commit ef4efe3
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I love the return types. Great job!
Note though that you are returning a charlist (single-quoted) in the error message while a string/binary (double-quoted) would be preferred:
iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,"Unable to import graph"}
josevalim
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View reviewed changes
Comment threadc_src/Tensorflex.c
 if (TF_GetCode(status) != TF_OK) {
 fprintf(stderr, "ERROR: Unable to import graph %s", TF_Message(status));
 return 1;
 return enif_make_tuple2(env,enif_make_atom(env,"error"),enif_make_string(env, "Unable to import graph", ERL_NIF_LATIN1));
@josevalimjosevalimMay 18, 2018•

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Just to clarify, an Erlang string is not the same as an Elixir string. So we need to use the binary API here.
Also, note that we can return a better error, so let's do that. Here are all of the possible error values from Tensorflow. The idea is to convert each of them into an atom. So if we get TF_NOT_FOUND, we should return {:error, :not_found}. This will probably be very common, so we can encapsulate it in a C procedure.
@anshuman23anshuman23May 18, 2018

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Noted. I completely agree-- I didn't realize I was returning char lists. Now I've shifted to enif_make_binary() wherever required. Also added this and the TF error codes to the latest PR.
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Merged all support functions into read_graph; returning atoms - #4
Merged
anshuman23 merged 1 commit into
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May 17, 2018
Merged
Merged all support functions into read_graph; returning atoms#4
anshuman23 merged 1 commit into
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dev
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@anshuman23
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May 17, 2018

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@josevalim as discussed in #3 , merged all graph reading capabilities into the read_graph function. This function returns a TF_Graph on successful loading of graph and an {:error,"Unable to load graph"} tuple on an unsuccessful attempt.
Example is as follows (classify_image_graph_def.pb is from Google's Imagenet model):
iex(1)>graph=Tensorflex.read_graph("classify_image_graph_def.pb")2018-05-1723:36:16.488469: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supportsinstructionsthatthisTensorFlowbinarywasnotcompiledtouse: SSE4.1 SSE4.2 AVX AVX2 FMA 2018-05-1723:36:16.774442: W tensorflow/core/framework/op_def_util.cc:334] OpBatchNormWithGlobalNormalization isdeprecated.It will cease to work inGraphDefversion9.Use tf.nn.batch_normalization().Successfullyimportedgraph#Reference<0.1610607974.1988231169.250293>iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,'Unable to import graph'}
I have an idea for the "story" around the graph loading we had talked about, so I'll be merging this PR as already discussed and adding the details of that in the next PR for your review.
@anshuman23
anshuman23
merged commit ef4efe3
into
masterMay 17, 2018
@josevalim
josevalim
commented
May 18, 2018

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I love the return types. Great job!
Note though that you are returning a charlist (single-quoted) in the error message while a string/binary (double-quoted) would be preferred:
iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,"Unable to import graph"}
josevalim
josevalim
reviewed
May 18, 2018
View reviewed changes
Comment threadc_src/Tensorflex.c
 if (TF_GetCode(status) != TF_OK) {
 fprintf(stderr, "ERROR: Unable to import graph %s", TF_Message(status));
 return 1;
 return enif_make_tuple2(env,enif_make_atom(env,"error"),enif_make_string(env, "Unable to import graph", ERL_NIF_LATIN1));
@josevalimjosevalimMay 18, 2018•

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Just to clarify, an Erlang string is not the same as an Elixir string. So we need to use the binary API here.
Also, note that we can return a better error, so let's do that. Here are all of the possible error values from Tensorflow. The idea is to convert each of them into an atom. So if we get TF_NOT_FOUND, we should return {:error, :not_found}. This will probably be very common, so we can encapsulate it in a C procedure.
@anshuman23anshuman23May 18, 2018

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Noted. I completely agree-- I didn't realize I was returning char lists. Now I've shifted to enif_make_binary() wherever required. Also added this and the TF error codes to the latest PR.
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, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Merged all support functions into read_graph; returning atoms - #4
Merged
anshuman23 merged 1 commit into
masterfrom 
dev
May 17, 2018
Merged
Merged all support functions into read_graph; returning atoms#4
anshuman23 merged 1 commit into
masterfrom 
dev
Conversation
@anshuman23
@anshuman23anshuman23
commented
May 17, 2018

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@josevalim as discussed in #3 , merged all graph reading capabilities into the read_graph function. This function returns a TF_Graph on successful loading of graph and an {:error,"Unable to load graph"} tuple on an unsuccessful attempt.
Example is as follows (classify_image_graph_def.pb is from Google's Imagenet model):
iex(1)>graph=Tensorflex.read_graph("classify_image_graph_def.pb")2018-05-1723:36:16.488469: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supportsinstructionsthatthisTensorFlowbinarywasnotcompiledtouse: SSE4.1 SSE4.2 AVX AVX2 FMA 2018-05-1723:36:16.774442: W tensorflow/core/framework/op_def_util.cc:334] OpBatchNormWithGlobalNormalization isdeprecated.It will cease to work inGraphDefversion9.Use tf.nn.batch_normalization().Successfullyimportedgraph#Reference<0.1610607974.1988231169.250293>iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,'Unable to import graph'}
I have an idea for the "story" around the graph loading we had talked about, so I'll be merging this PR as already discussed and adding the details of that in the next PR for your review.
@anshuman23
anshuman23
merged commit ef4efe3
into
masterMay 17, 2018
@josevalim
josevalim
commented
May 18, 2018

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I love the return types. Great job!
Note though that you are returning a charlist (single-quoted) in the error message while a string/binary (double-quoted) would be preferred:
iex(2)>graph2=Tensorflex.read_graph("Makefile"){:error,"Unable to import graph"}
josevalim
josevalim
reviewed
May 18, 2018
View reviewed changes
Comment threadc_src/Tensorflex.c
 if (TF_GetCode(status) != TF_OK) {
 fprintf(stderr, "ERROR: Unable to import graph %s", TF_Message(status));
 return 1;
 return enif_make_tuple2(env,enif_make_atom(env,"error"),enif_make_string(env, "Unable to import graph", ERL_NIF_LATIN1));
@josevalimjosevalimMay 18, 2018•

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Just to clarify, an Erlang string is not the same as an Elixir string. So we need to use the binary API here.
Also, note that we can return a better error, so let's do that. Here are all of the possible error values from Tensorflow. The idea is to convert each of them into an atom. So if we get TF_NOT_FOUND, we should return {:error, :not_found}. This will probably be very common, so we can encapsulate it in a C procedure.
@anshuman23anshuman23May 18, 2018

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Noted. I completely agree-- I didn't realize I was returning char lists. Now I've shifted to enif_make_binary() wherever required. Also added this and the TF error codes to the latest PR.
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